Securing investment is a pivotal moment; it represents a significant belief. Belief in you, your team, your product, and your vision. But that belief is just the down payment. What happens next determines whether you build Momentum or begin eroding the trust you’ve just earned.

The first 90 days after funding are not just another phase of a startup’s journey; they are the most consequential. These early days are where plans are tested, teams are aligned (or misaligned), and the tone for execution is set. This is a period of intense focus and action, where every decision can make or break your startup's future.

Why the First 90 Days Matter

Investors invest in a plan. Not just a pitch deck.

The clock starts ticking the moment the funds are deposited into your account. And it’s not about “doing everything”, it’s about doing the right things fast, decisively, and with clarity. This is your chance to show investors, your team, and the market that their confidence was justified.

If you get off to a strong start, you build confidence, secure future funding, and energise your team. However, a misstep, such as missed hires, unclear priorities, or a lack of progress, can quickly snowball into scepticism and hesitation.

1. Re-clarify the Vision and Plan

Once the term sheet is signed and the funds are wired, don’t assume that everyone remains perfectly aligned on the mission. Revisit your original strategy, but not through the lens of the pitch deck. Instead, translate that vision into a living, breathing execution plan.

Start by hosting a kickoff session with your leadership team. Reaffirm the company’s core objectives and how they align with the capital recently raised. Then, break your 12-month plan into three distinct arcs: the next 3 months (validation), 6 months (traction), and 12 months (scale). For each, define what success looks like: customer milestones, revenue targets, product metrics.

Strip out any roadmap features that were included to “look good” in the pitch. Focus on what drives real value.

💡 Tip: Frame your roadmap in terms of customer outcomes, not just features. A good feature shipped is meaningless if it doesn’t move user behaviour or business results.

2. Create a 90-Day Execution Plan.

Now that your roadmap is clean, zoom in. The first 90 days are your chance to build Momentum, reduce risk, and validate your direction. Break down your quarterly OKRs into weekly execution sprints.

This plan isn’t just a to-do list; it’s a forcing function for progress. It keeps your team accountable, helps you spot bottlenecks early, and creates a narrative of traction for both internal and external stakeholders.

❓Ask yourself: What can we show in 14 days that gives our investors confidence and sharpens our direction?

Use these wins as proof points in updates, board meetings, and recruiting conversations.

Capital brings confidence, but it also introduces the risk of waste. Just because a budget was outlined in the pitch doesn’t mean it’s the best plan today. Reevaluate.

Start with a “jobs to be done” audit for your capital. This means assigning every principal dollar amount a clear purpose: Will it help you grow faster? Will it de-risk something? Will it unlock the next round? This audit will help you prioritise and allocate your capital effectively.

Avoid spreading capital thin across too many initiatives. Stack your capital against your highest-leverage bets, those that have the potential to create step-changes in traction.

4. Make Key Hires Fast but Thoughtfully

Hiring post-funding is a paradox: you need to move quickly, but you can’t afford bad hires.

Start with roles that unlock other capabilities, such as technical leaders, senior product managers, or performance marketers. Prioritise people who bring leverage, not just output.

Build a fast, focused hiring sprint. Set clear scorecards, shorten your interview loops, and make onboarding part of your hiring checklist, not an afterthought.

⚠️ Warning: Don’t let speed compromise culture. Every early hire compounds, for better or worse.

5. Over-Communicate With Investors

Investor relations aren’t just a quarterly formality. Post-funding, your communication sets the tone for future support or scrutiny.

Set a monthly investor update rhythm. Use it to share wins, key metrics, hires, user feedback, and challenges. Be honest and specific. Include a clear “ask” if you need help.

Transparency earns trust. Even if growth is slower than expected, a founder who is proactive and data-driven earns far more goodwill than one who goes quiet.

🎯 Bonus: Investors who feel looped in are 10x more likely to make intros, share advice, and support the next round.

6. Get the Team on a Single Dashboard

Alignment starts with visibility. Every team member should know exactly what metrics matter and how the company is performing against them.

Build a shared dashboard with no more than 3–5 KPIs. These should be directly tied to your 90-day and quarterly goals, including user growth, retention, revenue, and feature usage. This shared dashboard fosters transparency and alignment within the team, ensuring everyone is on the same page.

Review this dashboard weekly during a standing team meeting. Use it to reinforce focus, reward progress, and adjust tactics.

7. Talk to Customers Weekly

No roadmap survives first contact with the customer. That’s why your post-funding phase should include a non-negotiable customer discovery loop. This loop involves scheduling weekly calls with prospects, active users, and churned customers. Use these insights to validate your positioning, refine your UX, and shape your roadmap.

Schedule weekly calls with prospects, active users, and churned customers. Use these insights to validate your positioning, refine your UX, and shape your roadmap.

Build in public when possible. Share learnings with your team and investors. Let customers see your velocity.

📣 Reminder: Every time you talk to a customer, you improve your ability to prioritise what matters.

8. Fix Operational Gaps Early

Now’s the time to tighten the bolts before scaling exposes the cracks. Audit your internal systems, including financial reporting, compliance, customer onboarding, analytics, and legal documentation.

Fix broken or manual workflows. Automate repeatable processes. Upgrade tools where needed.

Operational excellence doesn’t just reduce friction; it inspires confidence in investors, future hires, and partners.

9. Celebrate Wins, Loudly

Momentum isn’t just about metrics; it’s about morale. Wins, big or small, deserve spotlighting.

Did your new feature hit 70% adoption? Celebrate. Did a customer leave a glowing review? Please share it. Did a team member go above and beyond? Recognise them publicly.

Make a habit of celebrating progress. This fosters a culture of positivity, reinforces priorities, and maintains high energy when the road gets bumpy.

10. Define What “Winning” Looks Like

Ambiguity kills focus. Define a rallying point —a clear, simple goal that the entire company can unite around.

Instead of “increase retention,” say “hit 50% D30 retention by September.” Instead of “scale GTM,” say “acquire 20 new paying customers by Q2.”

Give your team something they can see, chase, and believe in.

What If You’ve Stumbled Out of the Gate?

Let’s be real: Not every post-funding runway starts with liftoff.

Maybe that key hire you celebrated on LinkedIn just isn’t working out. Perhaps your first central feature fell short, or worse, missed the deadline. Possibly, user growth is flat despite the burn rate. It happens. You’re building a company in the real world, not a slide deck.

But here’s the truth: it’s not the stumble that defines you. It’s the speed and honesty of your response.

1. Own It Fast and Fully

Don’t hide. Don’t spin. The moment you sense things are off, acknowledge it first internally, then externally. Great founders aren’t flawless; they’re self-aware.

Own the gap between what was expected and what’s happening. Lay out clearly what went wrong, what you’ve learned, and what changes you’re making.

💬 Example: “We hired for speed, but skipped culture fit. It slowed us down. We’ve paused additional hires to recalibrate our process. Here’s what we’re doing differently.”

This kind of honesty earns respect. It also keeps your team aligned and your investors engaged as allies, not sceptics.

2. Rebuild the Roadmap, Ruthlessly

Your original roadmap was built under assumptions that may no longer hold. Don’t waste time trying to “catch up” to a plan that no longer fits your current reality.

Strip the roadmap down to the essentials:

• What are the following 1–2 milestones that create validation?

• Which initiatives are high-effort, low-impact?

• What can be paused without damaging Momentum?

Get laser-focused on your next “proof point,” a signal that tells your team and investors we’re back on track.

📍Think: clarity over complexity. Speed to signal over feature completeness.

3. Launch a “Win Fast” Task Force

In moments of lost Momentum, nothing rebuilds morale like a quick, visible win.

Create a cross-functional squad (small and nimble) tasked with shipping something impactful in 7–10 days. It doesn’t have to be massive, just has to prove progress:

• A feature enhancement that removes friction

• A pilot with a new customer segment

• A landing page that converts

🎯 Momentum is emotional. A quick win builds confidence internally and creates a story for your next investor update.

4. Return to First Principles

When the plan stalls, go back to the source: the customer.

Block off time to personally talk to users, especially those who have churned or gone quiet. Ask:

• What’s the most significant pain you’re still solving manually?

• What did you hope our product would help with?

• What would make this indispensable?

Your goal isn’t to pivot out of desperation to re-anchor your roadmap in real, validated pain. This process often uncovers sharper positioning, more precise product focus, or surprising new paths to traction.

🧠 Founders who zoom out before zooming in again often find their most powerful insights.

5. Re-engage Investors with Clarity

What is the best way to recover investor confidence? Own the misstep and narrate your comeback.

Don’t ghost. Instead, send a focused update:

• Acknowledge the challenge.

• Share your diagnosis.

• Show what actions you’ve taken.

• Outline how you’re tracking progress.

• This turns a problem into a story of leadership. Savvy investors don’t expect perfection; they want to back founders who know how to adapt under fire.

🔁 Think of it as a strategic reset, not an apology.

Every startup stumbles. The best ones course-correct in days, not quarters.

If you’ve hit turbulence in the first 90 days, remember: your investors bet on you, not just your pitch. Show them you can navigate adversity, and you’ll earn even deeper trust than if everything had gone “according to plan.”

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This perspective is shared by Adam Ryan, a seasoned founder and investor with a deep track record in early-stage ventures, including some that have reached valuations exceeding $5 billion across Australia and California. With multiple startups launched and exited and hundreds more supported through investment and advisory roles at Watkins Bay and Monash University, Adam brings a unique insight into the world of startups and innovation.

Adam now serves as an Adjunct Professor at Monash University, ranked #9 globally for Economics, focusing on the intersection of innovation, startups, technology, start-up simulations, hyper-growth, Capital, and market disruption. One of his significant contributions is as the founder of the Startup Growth Hacking Resource Centre, a hub for emerging founders who want to scale with precision and purpose. This initiative connects him with the startup community, demonstrating his commitment to fostering innovation.

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A few years ago, I closed a funding round that, on paper, seemed like a dream. The terms were competitive. The lead had a well-known name.

However, in less than nine months, with the wrong CEO and the wrong board makeup, the deal no longer felt like a win; it felt like a mismatch.

We didn’t share the same vision for growing the company. Our board conversations started to feel completely disconnected, with little information flow.

That experience taught me one of the most valuable lessons in my founder journey:

Not all capital is created equal.

Raising money is important. But raising it from people who understand your values, believe in your mission, and are aligned on the journey is what sets companies up for long-term success.

Since then, I’ve become more intentional. I’ve learned to evaluate investors the same way I evaluate co-founders or senior hires. Not just for their name or their capital, but for their mindset, their behaviour under pressure, and their belief in how we build.

Over time, I’ve built a mental checklist of 10 critical dimensions I now use to assess investor fit before I say yes. These aren’t just theories. They stem from boardroom misalignments, poor advisors who lack the company’s best interests at heart, crisis calls, and a few incredible moments of partnership that remind me what great investor relationships can feel like.

If you’re raising now or plan to, I hope this framework is for you.

1. Values Alignment: Your First and Most Critical Filter

Before the term sheet, before the valuation, before the board seat, ask yourself a straightforward question:

Do we believe in the same things?

Values alignment is the invisible foundation of every strong founder-investor relationship. Without it, even the most well-funded startups fracture under pressure. With it, you get a partner who not only backs your strategy but also respects the way you build your business.

Start by getting clear on your own values: Do you prioritise transparency? Are you building with long-term impact in mind, rather than focusing on short-term sprints? Do you centre team well-being, ethical decision-making, or customer trust?

Now ask:

• Does this investor reflect those same values in their behaviour and track record?

• Do they respect how you lead, not just where you’re headed?

• Are they known to act with integrity during both boom times and boardroom crises?

This is about more than shared language about shared principles. For example, if you’re building a mission-driven company, an investor who only talks about market size and IRR (internal rate of return) might miss the deeper “why” behind your work.

You want someone who understands that how you grow matters just as much as how fast you grow.

From Experience: Speak with 2–3 portfolio founders of the investor. Ask them how the investor handled themselves during difficult conversations. That’s where values truly reveal themselves.

2. Cultural Fit: The Unspoken Deal Behind the Deal

Let’s be clear: cultural fit isn’t soft; it’s structural.

It determines how your startup makes decisions, handles tension, navigates ambiguity, and ultimately defines success. Culture is the operating system of your company, and when an investor plugs into it with the wrong mindset, the entire system risks misfiring.

Founders often evaluate culture when hiring, but forget to do the same with investors. That’s a mistake. Your cap table is an integral part of your company culture, particularly for the individuals who secure a seat on the board.

Here’s what to ask yourself:

• Do they communicate with respect, even when they challenge you?

• Do they appear as collaborators or as hands-off, controlling observers until things go wrong?

• Do they value Speed and risk, or depth and deliberation, and does that match how your team operates?

• How do they talk about failure? Blame game or learning moment?

When tough conversations inevitably arise on strategy pivots, hiring misfires, or missed targets, you need to know you can disagree without distrust. That’s cultural fit in action.

Don’t be blinded by prestige or pedigree. Suppose they create tension at every founder meeting, approach leadership with a zero-sum mindset, and prefer backchannels over direct dialogue. In that case, it’s a preview of what they’ll bring to your team dynamic.

Litmus Test: Ask yourself this: “Would I want this person in the room with me during my hardest week as a founder?”

If the answer is no, trust your instinct. The boardroom can either be your war room or your battlefield.

3. Domain Experience: Insight Is the Real Currency

Capital is abundant. Deep understanding is rare.

An investor who truly knows your space brings more than money; they get a second brain. They’ve seen the movie before. They know the plot twists. They understand the customer psychology, the regulatory landmines, the GTM bottlenecks, and the nuances that make or break startups in your vertical.

This matters for two reasons:

1. Strategic Insight

A domain-savvy investor can spot a signal in the noise. They’re not just reviewing your roadmap, they’re pressure-testing it with pattern recognition. They can help you prioritise what actually moves the needle in your market. They’ll save you cycles by helping you avoid dead ends they’ve seen before.

2. Credibility and Network

When they call a potential customer, advisor, or hire, they pick up. Their reputation in the space becomes a tailwind for your business. Whether it’s enterprise SaaS, digital health, fintech, or climate tech, having an investor who can open the right doors with context makes everything faster and smoother.

But this goes deeper than tactical help.

Domain expertise often breeds empathy. They get why your sales cycle is long. They understand the realities of burn rate in deep tech. They won’t panic when your ARR looks lumpy because they’ve seen the seasonal swings in your niche.

Red Flag: Be cautious of tourists-investors chasing trends who lack an understanding of your market dynamics. If they spend half the pitch meeting asking for definitions, that’s not a curiosity gap; it’s a capability gap.

From Experience: Ask them what trends they’re seeing in your space. Their answer will tell you whether they’re leading the wave or trying to surf one they don’t understand.

Choose investors who can challenge you because they understand your world, not in spite of it.

4. Strategic Alignment: Shared Vision, Shared Velocity

Raising capital isn’t just about funding your next chapter; it’s about ensuring the people backing you believe in the story you’re trying to tell.

Strategic alignment is about clarity on how you’re building, why you’re building it that way, and what success looks like over time. The best investors don’t just support your business, they help your approach to creating it.

Some investors are wired for blitz-scaling: rapid growth, land-grab tactics, and short runways between funding rounds. Others champion sustainable growth, characterised by measured hiring, capital efficiency, and strong unit economics from day one.

Neither path is inherently right or wrong. But what is wrong? Trying to pursue one strategy while your investors are pushing for the other.

You need alignment on questions like:

• Do we agree on when to prioritise profitability over growth?

• How aggressively should we approach customer acquisition and headcount?

• What role does brand, community, or product depth play in our GTM motion?

• Is this a 3-year sprint to acquisition, or a 10-year play for market leadership?

Misalignment here doesn’t just lead to tension; it leads to whiplash. Your team will feel it. Your roadmap will drift. And your energy will get sapped by trying to please two competing narratives. This can result in a loss of focus, wasted resources, and ultimately, a slower path to success.

Investor Fit Test: Ask how they’ve guided portfolio companies during moments of strategic inflection, such as a central pivot, pricing model change, or international expansion. Look for specific examples, their approach to risk management, and the outcomes of their guidance. Their answers will reveal how they think about strategic pacing and risk, and whether their approach aligns with your company’s needs and goals.

Reality Check: Some investors may attempt to modify your model to align with their thesis. Be wary. You want a partner who believes in your strategy and amplifies it, not one who tries to rewrite it from the sidelines.

When you align on strategy from the beginning, every board meeting becomes a working session, not a debate about first principles.

5. Exit Alignment: Build With the End (Clearly) in Mind

Every investor has an idea of what success looks like. The question is, does it match yours?

Exit alignment is one of the most overlooked yet high-stakes conversations a founder can have. It’s easy to skip it when term sheets are fresh and optimism is high. But failing to align on exit expectations early can lead to serious friction when stakes are highest at the finish line.

Investors have different return profiles depending on their fund structure, timelines, and incentives:

• A late-stage growth fund may target a 3–5x return over a shorter horizon and prefer companies that are primed for acquisition within a few years.

• A long-hold fund or mission-driven family office might support a slower-growth model with cash flow potential or eventual IPO.

• Some micro-VCs may be content with a solid $50 million exit, while others aim for billion-dollar outcomes.

Suppose your vision is to build a generational company that stays private for a decade. Still, your investors are counting on an exit in four years to return their funds. In that case, the misalignment will be evident in boardroom decisions, pressure on hiring, burn rate, and how aggressively you take or reject acquisition offers.

Ask direct questions:

• What is your expected holding period for investments like mine?

• What would be a successful outcome in your eyes, financially and strategically?

• How have you supported exits in the past? Did you drive the process, or let founders lead?

• How do you think about strategic buyers vs. IPO vs. private equity?

Insight: Don’t just ask these questions once. Revisit them as your business evolves. Exit alignment is a moving target, and strong investor relationships keep recalibrating over time.

Founder’s Note: You are not obligated to pursue their idea of success. But if you’re not aligned on that definition upfront, don’t be surprised when tension arises later.

When you and your investors share the same picture of the finish line, you can actually enjoy the race and navigate detours together without derailing the journey.

6. Leverage and Access: Capital is a Commodity. Access is the Multiplier

In today’s funding environment, capital is table stakes. What truly differentiates great investors is the leverage they provide beyond the wire transfer.

Ask any seasoned founder, and they’ll tell you: the proper intro at the right moment can be worth more than a million dollars. Whether it’s landing a pivotal enterprise customer, securing an all-star executive hire, or getting featured in a top-tier publication, access can change your company’s trajectory.

This is where elite investors earn their equity.

Look for investors who can:

• Open doors to customers – warm introductions to budget holders, not just “hey meet my friend” emails.

• Connect you to specialised talent – from VP-level operators to fractional CFOs, product leaders, and top-tier recruiters.

• Help shape your narrative – connecting you with media, PR experts, podcast hosts, or influencers in your ecosystem.

• Broker strategic partnerships – with other startups in their portfolio, distribution channels, or even potential acquirers.

But leverage isn’t just about who they know, it’s about how actively they use that network for you. Some investors have extensive Rolodexes but adopt a passive, reactive approach. Others are proactive partners who champion you behind closed doors without being asked.

Ask for examples:

• “Can you share examples of doors you’ve opened for other founders recently?”

• “Who in your network would you be excited to introduce us to in the next 6 months?”

Founder Tip: Pay attention to how they treat access during the fundraising process. If they’re already sharing intros and insights before a deal is signed, that’s a strong signal of how they’ll perform post-investment.

Capital is finite. Leverage is exponential. Choose investors who bring real influence, not just capital, and who are willing to spend their social capital on your success.

7. Track Record of Founder Support: Look at Their Behaviour When the Lights Dim

It’s easy to be supportive when everything’s going up and to the right.

But the accurate measure of an investor isn’t how they act when things are smooth, but how they show up when everything’s on fire. Do they stand shoulder-to-shoulder with founders through layoffs, pivots, failed experiments, or down rounds? Or do they go quiet, apply pressure, or look for the nearest exit?

Before you let someone onto your cap table, dig into their actual track record of providing founder support in the real world. Not just what they say during the pitch, but what they do when the headlines are gone.

Ask other founders:

• Were they present during challenging moments, or did they disappear?

• Did they offer clear-headed advice, or inject panic?

• Did they advocate for the team to other investors when things got tight?

• Were they supportive emotionally, not just strategically?

Support looks different at different stages. Sometimes it’s hands-on help with scenario planning. Sometimes it’s a quiet check-in call to say, “You’re doing great in there.” Great investors know when to coach, when to challenge, and when to listen.

Red Flag: Investors who only reference their “wins” and avoid discussing hard chapters with their portfolio companies may be hiding more than they’re sharing. If no founder has a nuanced story of how the investor responded to adversity, it’s a story in itself.

Green Flag: Founders who say, “They were the first call I made when everything was falling apart.”

Support during tough times doesn’t just preserve morale; it preserves momentum. And momentum is the lifeline of every startup.

Remember: You’re not just raising money. You’re choosing who gets to sit in your inner circle when your confidence is shaken and clarity is hard to find. Pick someone who won’t flinch when it’s time to get in the mud with you.

8. Follow-On Investment Ability: The Power of Staying Power

Raising your first round is hard. Raising the next round, especially during uncertain markets or slower-than-expected traction, can be even more challenging.

That’s why follow-on investment ability is one of the most critical, yet underrated, factors to evaluate in an investor. It’s not just about who gets you started; it’s about who has the conviction and capital to stay with you.

The reality is this: startups rarely follow a perfectly linear growth path. You’ll have valleys, not just peaks. Having investors who can and are willing to participate in future rounds can mean the difference between buying time to adjust your model or running out of runway mid-pivot.

Here’s what strong follow-on support can do:

• De-risk future rounds by providing early signals of internal participation, which builds confidence for outside investors.

• Shorten fundraising cycles, allowing founders to spend more time building and less time pitching.

• Identify key inflection points, such as expansion into new markets, hiring a core leadership team, or doubling down on a proven GTM strategy.

• Provide stability during uncertain times, when external capital is scarce or market sentiment turns conservative.

But follow-on ability isn’t just about having the funds, it’s about having the intent. Some investors reserve dry powder but rarely deploy it unless a round is oversubscribed. Others view follow-on support as a core part of their value proposition.

Questions to ask:

• “What percentage of your fund is typically reserved for follow-ons?”

• “What triggers your decision to double down in later rounds?”

• “Have you ever led or anchored a bridge round? Under what circumstances?”

• “How do you support companies that don’t hit immediate traction?”

From Experience: Talk to portfolio founders who didn’t raise huge rounds or massive valuations. Did the investor still show up? That’s where real intent is revealed.

Your investors should be willing to go the distance, not just for your breakout moments, but for the in-between chapters where belief matters more than metrics.

9. Speed and Decisiveness: Momentum Is a Competitive Advantage

Fundraising is already an emotionally and operationally draining process. The last thing a founder needs is an investor who stalls the process with vague signals, excessive hand-wringing, or endless “checking with the partnership” cycles.

Enter the slow nothe investor who strings you along with interest but no conviction. They take multiple meetings, ask for unnecessary diligence upfront, and seem excited… until they ghost you or pass weeks later with “we’ll stay close.”

That kind of behaviour isn’t just frustrating; it’s also harmful. It drags out your timeline, can slow down momentum with other investors, and erodes your ability to lead the round with confidence.

In contrast, great investors are decisive and responsive. They know what they’re looking for, they’re transparent about their internal process, and they move quickly when they see alignment.

Why is this important as a Founder?

• Time is your most limited asset. Every week spent chasing uncertain capital is a week not spent building product, closing deals, or hiring the team you need.

• Investor behaviour during the raise reflects their post-investment style. Fast decision-makers are often better board members, as they are efficient, clear, and action-oriented.

• Speed builds momentum. Early commitments from decisive investors create social proof, which encourages others to take a stand and helps rounds close faster.

Evaluate their decision rhythm:

• “How long do you typically take from the first meeting to a decision?”

• “Who else is involved in sign-off, and what’s the process?”

• “How many deals have you led in the past year, and what was the average timeline?”

Red Flag: If they can’t clearly articulate how decisions get made or if they keep moving the goalposts, they’re likely not conviction-driven. You don’t want that energy on your cap table.

Green Flag: Investors who do their homework, ask thoughtful (not performative) questions, and come back with a clear yes or no within days, not weeks.

Founders operate in a world of urgency. Your capital partners should, too.

10. Reputation in the Ecosystem: Who You Raise From Shapes How You’re Seen

When you take on capital, you’re not just adding money to your balance sheet; you’re adding a name to your story. An investor’s reputation becomes part of your brand narrative. Their reputation walks into every room with you, whether you realise it or not.

That’s why it’s critical to ask: What does this investor’s name signal in the broader ecosystem?

Strong reputations bring signal, credibility, and leverage:

• Other investors take note. A respected investor on your cap table can help you attract high-quality capital in future rounds.

• Operators take your calls. Great talent is more likely to join a startup backed by someone they admire or trust.

• Acquirers and strategic partners listen more closely. Institutional trust opens doors that pitch decks alone can’t.

But reputation cuts both ways.

A poorly regarded investor, one known for founder-unfriendly terms, erratic behaviour, or post-investment disengagement, can cast a long shadow over your company. You might not feel it immediately, but when your next round gets harder than it should or a key hire hesitates, the whispers in the ecosystem matter.

What to dig into:

• How do other founders describe their experience with this investor?

• How do they behave in challenging moments? Are they known for pushing founders too hard or abandoning ship?

• Are they seen as value-add, or valuation-obsessed?

• Do they have healthy relationships with co-investors and board members? Or is there a pattern of friction?

Founder Tip: Don’t just look at their LinkedIn endorsements or media presence. Discuss privately with multiple founders, especially those whose companies didn’t scale quickly. That’s where an honest reputation is earned.

Warning Sign: If a firm has a flashy name but portfolio companies consistently say, “They looked great on paper, but…” listen to that instinct.

Your cap table is social capital. Build it with people whose names add trust, not tension.

Choosing an investor is one of the most critical decisions a founder will make. It’s not just about who wires the money; it’s about who earns a seat at your table, shapes strategic decisions, and stands beside you when things don’t go to plan. The best investors are not just capital providers, they’re conviction partners. They align with your values, your pace, and your long-term vision. They challenge you without undermining you. They offer leverage, not just oversight.

So take your time. Ask the uncomfortable questions early. Speak to portfolio founders. Watch how investors behave when you’re not at your peak. Because once the term sheet is signed, you’re in it together for better or worse. And in the high-stakes world of building a company, the right investor doesn’t just help you grow; they help you grow the right way. Choose wisely. Your future self and your team will thank you.

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This perspective is shared by Adam Ryan, a seasoned founder and investor with a deep track record in early-stage ventures, including some that have reached valuations exceeding $5 billion across Australia and California. With multiple startups launched and exited and hundreds more supported through investment and advisory roles at Watkins Bay and Monash University, Adam brings a unique insight into the world of startups and innovation.

Adam now serves as an Adjunct Professor at Monash University, ranked #9 globally for Economics, focusing on the intersection of innovation, startups, technology, start-up simulations, hyper-growth, Capital, and market disruption. One of his significant contributions is as the founder of the Startup Growth Hacking Resource Centre, a hub for emerging founders who want to scale with precision and purpose. This initiative connects him with the startup community, demonstrating his commitment to fostering innovation.

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I hope you enjoyed this article.

If this sparked some thinking (or challenged a few assumptions), here’s how you can help me help more Founders and Start Up teams:

Follow me on LinkedIn for regular insights on startup growth, founder psychology, venture capital trends, real-world tactics and more

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A few months ago, a founder shared a story with me that I still think about.

"Our AI was outperforming everything else in the market but we still couldn't close the round. The VCs loved the product. Then the legal team got involved."

The deal didn't fall apart due to the technology, market opportunity, or metrics. It stalled because of one simple yet critical question:

"Who owns the data this was trained on?"

That single question changed everything.

In 2025, legal and ethical due diligence isn't just a checkbox—it's a gating function. And for AI startups, it's far more complex than most founders realise. Investors are not just evaluating your product's performance, but also what lies beneath it, such as your data sources, compliance frameworks, and ability to navigate a rapidly evolving regulatory landscape[1][4].

For founders, this shift represents both a challenge and an opportunity. Those who prepare thoroughly can turn diligence into a competitive advantage, inspiring confidence and closing rounds faster. Those who don't? They risk losing trust and dealing in an instant[3][6].

Why Legal Due Diligence in AI Is Different

Let's start with what most founders know: traditional startup due diligence is relatively straightforward. Investors want clean cap tables, properly executed contracts, clear IP assignments, and basic corporate hygiene.

However, AI startups are a different breed entirely. When you build AI systems, you're not just selling code but creating technologies that learn, adapt, and make decisions based on real-world data. These systems interact with people and environments in ways that are often opaque and unpredictable[1][4][8].

This complexity introduces a new layer of risk and a new set of questions from investors:

• Who owns the algorithm? Did your team build it from scratch, or does it rely on open-source components?

• Where did the training data come from? Was it licensed? Scraped? Provided by customers?

• What are the ethical risks? Could your model be biased or discriminatory?

• Are you compliant with privacy laws like GDPR?

• Does your technology fall under national security regulations?

These aren't theoretical concerns; they're real issues that can derail deals if left unaddressed[2][4][6]. But here's the good news: with the right preparation, these challenges are navigable. Let's break down six of the biggest red flags investors look for and how you can address them head-on.

1. Who Owns the AI? (IP Rights & Data Moats)

This is always where due diligence begins and where things often unravel. Intellectual property (IP) ownership is foundational to any tech investment, but it's especially critical in AI startups, where proprietary algorithms and data moats are key drivers of value[1][4].

Investors will want clear answers to questions like:

• Is your algorithm proprietary or open-source?

• Were all contributors employees, contractors, and collaborators—properly assigned IP rights?

• Do you own the outputs generated by your model?

• What rights do you have to the training data?

For example, under UK copyright law, AI-generated content is only protected if an identifiable party is responsible for its creation. Similarly, patent protection requires specific technical contributions that must be well-documented[1][6]. Without clarity on these points, investors may see your IP as vulnerable or, worse, legally indefensible.

Founder Tip:

Have every contractor and contributor sign airtight IP assignment agreements from day one. Maintain detailed version history and architecture documentation for your algorithms. Keep meticulous records of every dataset you use, including its source, licensing details, and any restrictions on its use[1][4].

2. Is the AI GDPR compliant? (Data Usage & Privacy Law)

Data privacy laws, such as GDPR, are among the most common hidden landmines in AI startups, and they're not going away anytime soon. Many founders assume that publicly scraped data is "safe" to use for training models, but under GDPR, even publicly available content can qualify as personal data if it relates to an identifiable individual[2][4].

The risks don't stop there:

• If you've trained models on customer data without explicit consent or suitable anonymisation protocols, you could violate GDPR[2].

• If your product captures sensitive user data, such as biometrics or behavioural analytics, you may be subject to even more stringent legal obligations[4][6].

Founder Tip:

Conduct regular Data Protection Impact Assessments (DPIAs) to identify and mitigate privacy risks early on. Anonymise or pseudonymise datasets wherever possible to reduce exposure. Build opt-in consent mechanisms into your product from day one; it's easier than retrofitting compliance later[2][4].

3. The NSIA Trap: Is Your Tech a National Security Risk?

This one catches many founders off, especially those operating in sensitive sectors like defence or surveillance technologies. Under the UK's National Security and Investment Act (NSIA), certain types of AI fall under "sensitive sectors" that require pre-approval for fundraising or M&A activity[1][3].

If your technology can:

• Detect or track objects or individuals

• Control autonomous physical systems (e.g., drones or vehicles)

• Interface with critical national infrastructure

…you may need government clearance before proceeding with certain transactions[1][3][6].

This process can delay deals—or even block them altogether if not handled proactively.

Founder Tip:

If your technology operates in regulated domains, consult legal experts familiar with NSIA compliance early in your fundraising process. Include documentation in your data room explaining how your product aligns with or avoids regulated uses[1][3].

Useful Checklist

Here’s a practical checklist to help you build trust during due diligence:

✅ Confirm IP assignments for all contributors

✅ Catalogue your data sources and licenses

✅ Document GDPR compliance and user consent

✅ Check if you fall under NSIA or sector-specific regulation

✅ Create an ethics log: bias testing, explainability, safeguards

✅ Audit your open-source stack and clean up risky licenses

✅ Include liability frameworks in your product documentation

Final Thoughts

Here’s the thing no one tells you early on:

Diligence doesn’t kill deals—surprises do.

In AI, your greatest strength may be your technical expertise. However, your greatest risk is what’s hiding underneath it. Therefore, Founders who take legal and ethical diligence seriously don’t just avoid delays.

1. They inspire confidence.

2. They close faster.

3. They earn more trust.

And they send a powerful signal to the market:

We’re not just building fast—we’re building right.

I hope you enjoyed this article.

If this sparked some thinking (or challenged a few assumptions), here’s how you can stay connected and go deeper:

Follow me on LinkedIn for regular insights on startup growth, founder psychology, venture capital trends, real-world tactics and more

Subscribe to the LinkedIn Newsletter to get fresh, founder-first content in your inbox—no fluff, just the strategies and stories that matter.

Check out the Start Up Growth Hacking Resource Centre – it’s packed with articles, podcasts, curated lists, legal templates, fundraising tools, and proven playbooks for founders ready to start, grow, and scale smarter. You can find the link to the Resource Centre page on my profile.

#AIstartups #duediligence #legalcompliance #ethicalAI #GDPR #IPrights #AIregulations #investorreadiness #AIcompliance #nationalsecurity #AIethics #AIinvestment

References and Further Reading

[1] AI: Conducting legal, due diligence – Law services | EY - Australia https://www.ey.com/en_au/insights/law/ai-conducting-legal-due-diligence-law-services

[2] AI Compliance: A Must-Read for Fintechs Using AI - InnReg https://www.innreg.com/blog/ai-compliance-a-must-read-for-fintechs-using-ai

[3] 5 Essential Due Diligence Red Flags That AI Can Help Uncover https://www.linkedin.com/pulse/5-essential-due-diligence-red-flags-ai-can-help-uncover-skylarkai-mz01e

[4] AI Due Diligence: Key Steps, Best Practices & Checklist [GUIDE] https://redblink.com/ai-due-diligence/

[5] [PDF] Compliance Costs of AI Technology Commercialization - arXiv https://arxiv.org/pdf/2301.13454.pdf

[6] Spotting Red Flags in Due Diligence | AI-Powered Risk Detection https://www.aracor.ai/blog/spotting-red-flags-in-due-diligence

[7] [PDF] An Analysis of AI Integration in the Context of Mergers and ... https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=9155896&fileOId=9155897

[8] AI Due Diligence: What It Is and How It's Changing M&A - Grata https://grata.com/resources/ai-due-diligenc

Valuation is a substantial challenge for AI startup founders, particularly when the technology is evolving rapidly. Capital needs are urgent and significant when training AI systems. To address these challenges, founders and investors often use flexible funding structures, primarily convertible notes and direct equity, to balance speed, flexibility, and control[1][2][4].

Why is this Important for AI Startups

AI startups typically require significant capital before generating revenue, as funds are needed for model training, hiring, infrastructure, and data acquisition[3]. Traditional equity rounds can be slow and risky, particularly when a startup’s valuation is complex and difficult to determine early on. Convertible loan notes (CLNs) and Simple Agreements for Future Equity (SAFEs) are popular because they allow founders to raise capital without immediately setting a valuation or giving up too much equity[3][7].

Convertible Notes: The Fast Track

Convertible notes are short-term loans that convert into equity during a future priced round, such as the next major funding event[1][2][4][5]. Key features include:

Deferred valuation: The company’s value is set in the next round, not at the time of the note[1][2][4].

Discount or valuation cap: Investors receive a lower price per share when converting as a reward for early risk[1][4][5][8].

Maturity date: If no qualifying round occurs, the note may demand repayment or renegotiation. [1][4][5]

Interest: Some notes accrue interest (typically 5–8%), which also converts into equity[1][4][5].

Convertible notes can work well. However, multiple required investment rounds can result in significant dilution.

Direct Equity: Setting the Price Early

Equity rounds involve setting a fixed valuation and issuing shares immediately. This process provides a transparent ownership structure and more substantial investor commitment. Still, it is slower and riskier for pre-traction startups, as it requires more due diligence and legal documentation[6]. Founders often avoid priced rounds before achieving product-market fit or accumulating proprietary data. Still, equity becomes more strategic as the company matures[6].

Why Valuation Is Harder in AI

Raising capital for AI startups is uniquely challenging because:

Investor fatigue: Many similar AI pitches make differentiation difficult[3].

Data as a differentiator: Startups using open models and public APIs are judged more on go-to-market execution than technical novelty[3].

No clear benchmarks: Enterprise AI sales cycles are long, and consumer AI retention is uncertain, making it hard to define “traction”[3].

Founders should focus on demonstrating market demand, early usage, and a defensible data strategy rather than overselling technical capabilities[3].

Protecting Your Runway in the Term Sheet

Long-term risks are embedded in the term sheet regardless of the financing structure. Key clauses to watch include:

1. Conversion triggers: Ensure founder(s)./ control when notes convert, especially in bridge rounds[1][4].

2. Discount stacking: Limit cumulative discounts to avoid excessive dilution[2][4][5].

3. Valuation cap negotiations: A low cap can lead to significant dilution if the company’s value increases rapidly[1][4][5][8].

4. Redemption rights: Avoid clauses that could force repayment or liquidity events[1].

5. Warranties & founder liability: Clearly define what constitutes a forecast versus a binding promise, which can be ambiguous in AI[1].

Final Thoughts

In AI, speed is essential, but so is survivability. Founders who treat financing as a strategic tool—not just a source of capital—are better positioned to build resilient businesses. The choice between convertible notes and equity should align with your company’s momentum, risk profile, and team strengths. Ultimately, your most significant leverage lies not just in your technology but in how you structure your business around it[1][2][4][5][7].

I hope you enjoyed this article.

If this sparked some thinking (or challenged a few assumptions), here’s how you can stay connected and go deeper:

Follow me on LinkedIn for regular insights on startup growth, founder psychology, venture capital trends, real-world tactics and more

Subscribe to the LinkedIn Newsletter to get fresh, founder-first content in your inbox—no fluff, just the strategies and stories that matter.

Check out the Start Up Growth Hacking Resource Centre – it’s packed with articles, podcasts, curated lists, legal templates, fundraising tools, and proven playbooks for founders ready to start, grow, and scale smarter. You can find the link to the Resource Centre page on my profile.

Download Calculator

References and Further Reading

[1] Convertible Notes: Understanding the Debt and Equity Hybrid https://www.biztechlawyers.com/legal-articles/guide-to-convertible-notes

[2] Convertible Notes Explained: Should You Use Them for Funding https://nextround.ai/2024/12/09/convertible-notes-explained-should-you-use-them-for-funding/

[3] Day 9: Alternative Funding Strategies for AI Startups - LinkedIn https://www.linkedin.com/pulse/day-9-alternative-funding-strategies-ai-startups-more-olojede-zcn0f

[4] Convertible Notes: The Complete Guide for Startups - Cake Equity https://www.cakeequity.com/guides/convertible-notes

[5] https://breakingintowallstreet.com/kb/venture-capital/convertible-notes/

[6] Funding Strategies for AI Startups: Tips from the Pros - SkyNet AI https://skynetai.dev/blog/funding-strategies-for-ai-startups--tips-from-the-pros

[7] How Can Convertible Notes Help My Startup? - LegalVision https://legalvision.com.au/startup-lawyer-series-convertible-note-work/

[8] How Do Convertible Notes Work? - HelloData https://www.hellodata.ai/help-articles/how-do-convertible-notes-work

#AIStartups #FundraisingTips #ConvertibleNotes #EquityRounds #StartupFinance #EarlyStageVC #CapTableStrategy #FounderTips #TermSheet101 #AIFinancing #StartupLaw #VentureCapital #SeedFunding #BuildSmart #StartupPlaybook

As a founder, you’ve probably heard investors talk about pre-money and post-money valuations. You might even know your “cap table” needs to be updated after each raise. But do you know precisely how your ownership changes as a result?

Let’s break it down simply — no jargon, no legalese — just clarity.

🧠 What Is Pre-Money vs. Post-Money Valuation?

• Pre-money valuation is how much your company is worth before the new money comes in.

• Post-money valuation is how much your company is worth after adding the new investment.

Here’s the simple formula:

Post-Money Valuation = Pre-Money Valuation + Investment Amount

👉 Example:

If your company has a pre-money valuation of $4 million, and an investor puts in $1 million. In that case, the post-money valuation becomes $5 million.

🔍 So, What Does That Mean for You as a Founder?

When you raise money, you’re issuing new shares to investors. You’re not handing over your own — you’re making more of the pie. But that means your slice gets smaller.

This is called dilution:

The reduction in ownership percentage that happens when new shares are issued.

🍕 The Startup Pie Analogy

Imagine your company is a pizza with 100 slices (shares). You and your co-founder own all of it.

Now, you bring in an investor who wants 20% of the company.

To do that, you don’t take slices off your plates; you bake more pizza. You issue new slices, bringing the total to 125 slices. The investor gets 25 slices (20%), and you own less than before.

You didn’t lose slices — but you now own a smaller percentage of the whole.

📉 How to Calculate Dilution

Let’s walk through an example:

• You and your co-founder own 1,000,000 shares total.

• Your startup is valued at $4M pre-money.

• You raise $1M from a VC.

• That investor wants 20% of the company.

To give them 20% after the round, you issue:

Now the cap table looks like this:

You’ve been diluted from 100% ownership to 80%.

⚠️ Is Dilution a Bad Thing?

Not necessarily. Not necessarily. Dilution is expected — and sometimes necessary — to grow faster, hire better, and create a more significant outcome for everyone.

What matters is what the money enables.

If 20% dilution helps grow your business 10x, you’ll be better off with a smaller slice of a much bigger pie.

But you do need to:

• Understand how much you’re giving away

• Model multiple rounds of dilution

• Keep an eye on your future ownership (especially if you’re planning Seed → Series A → Series B, etc.)

🛠 How Founders Can Stay Smart About Dilution

• Model your cap table before and after each round.

• Always compare equity given to the value gained.

• Think long-term: avoid over-diluting early when valuations are low.

• Don’t get too fixated on % ownership — instead, focus on increasing company value and alignment with your investors.

🧭 Final Thought

Raising capital is more than closing a round—it is choosing your partners and reshaping your company’s future. The best founders understand not just how much money they’re raising but also

Dilution isn’t the enemy — confusion is.

Get clear on the math, and you’ll stay in control of your own story.

Download Calculator

I hope you enjoyed this article.

If this sparked some thinking (or challenged a few assumptions), here’s how you can help me help more Founders and Start Up teams:

Follow me on LinkedIn for regular insights on startup growth, founder psychology, venture capital trends, real-world tactics and more

Subscribe to the LinkedIn Newsletter to get fresh, founder-first content in your inbox—no fluff, just the strategies and stories that matter.

Check out the Start Up Growth Hacking Resource Centre – it’s packed with articles, podcasts, curated lists, legal templates, fundraising tools, and proven playbooks for founders ready to start, grow, and scale smarter.

It would be awesome if you could recommend the Start Up Growth Hacking Resource Centre and share it with others.

Raising capital feels like a milestone — and it is.
But it’s also the moment where the real math begins.

Access to Free Dilution Calculator Below

Many founders talk about pre-money and post-money valuations. Fewer understand precisely how that impacts their ownership.

Let’s break it down with no jargon, just clarity.

🧠 Pre-Money vs. Post-Money?

Pre-money = company value before investment
Post-money = pre-money + new investment

Example:
$4M pre-money + $1M raise = $5M post-money

🍕 What’s Dilution?

When you raise money, you issue new shares to investors.
You don’t lose your shares, but your percentage ownership shrinks.

Imagine your company as a pizza with 100 slices. You and your co-founder own it all.

An investor wants 20%. You bake more pizza — total slices = 125.

The investor gets 25 slices. You now own 80%, not 100%.

That’s dilution — and it’s not bad if the money fuels real growth.

📉 How to Stay Smart

Dilution becomes a problem only when it’s misunderstood.

Founders should:
✅ Model the cap table before & after each round

✅ Understand what they’re giving up — and gaining

✅ Avoid over-diluting too early

✅ Focus on growing total value, not just keeping %

✅ Think ahead: Seed → Series A → B → Exit

🧭 Clarity Is Power

Dilution isn’t the enemy. Confusion is.

The best founders own the math and shape the outcome.
You’re not just raising funds — you’re choosing partners and trading equity for acceleration. Done well, it’s worth it.

📊 Want a Free Dilution Calculator?

Download Calculator

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Two years ago, being an AI founder meant being ahead of the curve. Today, you're right in the thick of it and the curve is moving faster than ever. Venture capital (VC) funding for AI startups has surged dramatically, with global investments exceeding $100 billion in 2024, marking an 80% increase from $55.6 billion in 2023[1][7]. But this isn't another speculative hype cycle like crypto or direct-to-consumer (DTC) brands. This time, the stakes are higher, the questions tougher, and the focus sharper.

Across these conversations, one thing has become clear: the next decade will belong to founders who treat AI not as a buzzword but as a transformative tool to solve real, urgent problems. If you're building or planning to raise capital in this space, here's what you need to know about why VCs are doubling down on AI and how you can rise to meet this moment with inspiration and motivation.

AI Is No Longer Experimental: It's Foundational

Not long ago, AI was relegated to R&D departments a curiosity rather than a necessity. It was experimental, often siloed off from core business operations. Fast-forward to 2025, and that era is over. AI has become a foundational infrastructure across industries. It powers fraud detection systems in banking, predictive engines in logistics, and customer service workflows in the enterprise worldwide[2][4]. Much like how cloud computing reshaped business operations over the last two decades, AI is now transforming decision-making.

For example:

Banks are using real-time AI systems to detect fraud and manage compliance risks more effectively[5].

Logistics companies are deploying predictive engines to anticipate supply chain disruptions before they occur[2].

Enterprises are integrating AI into customer service workflows to resolve queries faster and more accurately[4].

This means that founders will no longer be able to build gimmicks or one-off tools. Investors want startups that develop essential systems and tools that feel as integral to a business as its ERP, Accounting or CRM software.

Legacy Sectors Are Finally Waking Up

For years, industries like legal, finance, healthcare, and logistics were considered too slow-moving or complex for meaningful AI adoption. They were seen as resistant to change bogged down by legacy systems and regulatory hurdles. But that perception has shifted dramatically in recent years.

These sectors are now embracing AI with urgency:

Law firms are using natural language processing (NLP) tools to automate contract reviews, cutting hours of manual work down to minutes[3].

Healthcare providers leverage AI for early diagnoses and personalized treatment plans[6].

Logistics companies have adopted predictive analytics to optimize routes and reduce delays[2].

What's driving this shift?

These industries are massive and under-digitised, a perfect storm for innovation. They're also hungry for solutions tied directly to revenue generation or risk reduction.

For example:

In finance, real-time fraud detection powered by AI saves banks millions yearly[5].

Predictive engines reduce costly delays in logistics while improving customer satisfaction[2].

For founders targeting these verticals, the opportunity is immense. You're not late, you're early enough to capture significant market share in industries that are only beginning their digital transformation journeys.

Data Moats Are the New Defensibility

In the early days of AI investment, startups could train on open-source datasets and call their models "proprietary." Those days are gone. Today's investors ask one critical question: "What gives this company an unfair advantage in data?"

Proprietary data has become the most valuable asset for any AI startup. Whether it's exclusive access to real-time customer data or highly specialized datasets that competitors can't replicate a strong data moat is now essential for defensibility[1][7]. You risk becoming a commodity in an increasingly crowded market without control over your data pipeline.

Consider this: if two startups build similar models, but one can access unique datasets, anonymised patient records for healthcare diagnostics or real-time shipping data for logistics optimization, that startup will always have an edge. Investors know this and are prioritizing companies with robust data acquisition strategies.

Key takeaway If you don't own your data, you don't own your outcome.

Early Traction Beats Academic Brilliance

A few years ago, having a PhD or publishing papers at top conferences like NeurIPS was enough to secure funding. Not anymore. VCs today prioritize traction over credentials. They want evidence that your product works in the real world:

Do users come back after week one?

Are you shipping updates quickly?

Is there clear proof that your product solves a painful problem?

Founders who can demonstrate early adoption and measurable outcomes, no matter how small, are far more fundable than those relying solely on academic pedigree[1][7].

The Decline of “ChatGPT-for-X” Pitches

Remember when every other pitch was "ChatGPT-for-X"? That moment has passed. Investors are fatigued by thin wrappers around large language models (LLMs) with minimal defensibility or differentiation.

Capital Efficiency Is Back in Fashion

The era of hypergrowth-at-all-costs is over. Capital efficiency is more important than ever in today's post-ZIRP (zero interest rate policy) world. Founders who can do more with less by building modularly, focusing on unit economics, and hiring small but high-leverage teams are winning investor confidence[1][7].

Strategic M&A Is Unlocking Faster Exits

One underappreciated trend is the rise of early-stage acquisitions by major enterprises like Salesforce and Adobe. These companies can't afford to fall behind in the AI race and are acquiring startups earlier, sometimes at Seed or Series A stages[7].

Ethics and Explainability Are Non-Negotiable

AI governance has moved from a footnote to a focal point in investor discussions. Issues like bias mitigation, model explainability, and data privacy are now deal-breakers if not adequately addressed[5][6].

The Timing Has Never Been Better

This isn't another bubble; it's a tipping point. The infrastructure is mature, markets are ready, and capital is flowing selectively. Founders who focus on solving real problems with lean teams and sharp execution are perfectly positioned to seize this moment.

I hope you enjoyed this article.

If this sparked some thinking (or challenged a few assumptions), here’s how you can stay connected and go deeper:

Follow me on LinkedIn for regular insights on startup growth, founder psychology, venture capital trends, and real-world tactics.

Subscribe to the LinkedIn Newsletter to get fresh, founder-first content in your inbox, no fluff, just the strategies and stories that matter.

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References and Related Reading

1. CB Insights (2025). State of Venture 2024 Report: Insights and Advisory. Available at: [https://www.twofourseven.co.uk/blog/cb-insight-state-of-venture-2024-report-insights-and-advisory](https://www.twofourseven.co.uk/blog/cb-insight-state-of-venture-2024-report-insights-and-advisory)

2. The Code Work (2025). How Data Analytics & AI Are Transforming 3PL Industry. Available at: [https://thecodework.com/blog/how-data-analytics-ai-are-transforming-3pl-industry/](https://thecodework.com/blog/how-data-analytics-ai-are-transforming-3pl-industry/)

3. BIICL (2025). Use of Artificial Intelligence in Legal Practice. Available at: [https://www.biicl.org/documents/170_use_of_artificial_intelligence_in_legal_practice_final.pdf](https://www.biicl.org/documents/170_use_of_artificial_intelligence_in_legal_practice_final.pdf)

4. Thrive Strategy (2024). AI Insights from McKinsey's Latest Report. Available at: [https://www.thrivecs.com/insights/ai-insights-from-mckinseys-latest-report](https://www.thrivecs.com/insights/ai-insights-from-mckinseys-latest-report)

5. PwC UK (2025). AI in Financial Services: Navigating Risk & Opportunity. Available at: [https://www.pwc.co.uk/industries/financial-services/understanding-regulatory-developments/ai-in-financial-services-navigating-the-risk-opportunity-equation.html](https://www.pwc.co.uk/industries/financial-services/understanding-regulatory-developments/ai-in-financial-services-navigating-the-risk-opportunity-equation.html)

6. Accenture (2025). Technology Vision 2025: Healthcare & Emerging Technologies. Available at: [https://www.accenture.com/us-en/blogs/health/accenture-technology-trends-2025-healthcare](https://www.accenture.com/us-en/blogs/health/accenture-technology-trends-2025-healthcare)

7. Kamaflow (2025). Global Venture Capital Market Summary 2024. Available at: [https://kamaflow.com/en/post/the-largest-analytical-agencies-summarize-the-results-of-2024-for-the-global-venture-capital-market/](https://kamaflow.com/en/post/the-largest-analytical-agencies-summarize-the-results-of-2024-for-the-global-venture-capital-market/)

#ArtificialIntelligence #AIStartups #VentureCapital #TechInnovation #DataDriven #AIInvestments #StartupFunding #MachineLearning #TechTrends2025 #Entrepreneurship #AIApplications #FutureOfWork #BusinessStrategy #DeepTec

Evaluation Differences Now and Then

Venture capitalists (VCs) evaluate the potential of AI startups today with a more disciplined and practical approach than a few years ago, as you would expect. This shift echoes lessons learned from earlier investment cycles, growing market dynamics, and the need for sustainable growth.

It got me thinking about this evolution and the differences between 2025 and now. How have they evolved, and what challenges are VCs facing with this fast-changing investment vertical?

1. The Transition from Hype to Practicality: A Key Shift in VC Evaluation

Then: (Pre-2025): VCs were heavily influenced by the hype around cutting-edge technology, often funding startups based on innovative algorithms or technical expertise without requiring clear business applications or ROI. Startups with buzzwords like "machine learning" or "neural networks" could secure funding even if their product-market fit was unclear[1][8].

Now: VCs prioritise startups solving specific, high-value problems with measurable outcomes. They demand proof of ROI, such as demonstrated cost savings or revenue generation. For example, startups automating hospital billing or fraud detection are more likely to secure funding than those offering vague promises of AI-powered transformation[1][3][8].

2. The Rise of Data as a Core Asset: A Fundamental Shift in VC Evaluation

Then: Investors focused on the uniqueness of AI models and technical complexity, often overlooking the quality and ownership of underlying datasets[1][5].

Data has become a critical differentiator. VCs assess a startup's data relevance, accuracy, and legality. Proprietary, high-quality datasets are now essential for building defensible AI solutions. Startups counting on open-source or public datasets encounter greater scrutiny due to concerns about scalability and future challengers[2][5].

3. Ethical AI and Regulatory Compliance: A New Standard in VC Evaluation

Then: Ethical considerations and regulatory compliance were often afterthoughts in VC evaluations. Startups were rarely asked about bias mitigation, privacy protocols, or compliance with laws like GDPR[1][8].

Now: Ethical AI practices and regulatory readiness are deal-breakers. VCs actively audit startups for transparency, fairness, and compliance with legal standards. Questions like "How do you mitigate algorithmic bias?" and "Can regulators shut you down?" are now central to due diligence processes[1][10].

4. Business Model Viability

Then: Startups were funded based on potential market size and growth projections rather than clear monetisation strategies. Early traction, such as free user adoption or pilot programs, was often enough to secure investment[1][8].

Now: VCs demand robust business models with clear revenue streams. Startups must illustrate how they plan to monetise their solutions—whether through subscription fees, API usage charges, or enterprise contracts—and show evidence of market demand[1][3][10].

5. Team Composition

Then: Teams with strong technical credentials (e.g., PhDs or ex-Big Tech engineers) were prioritised over operational expertise. A technically impressive team was often considered sufficient for securing funding[1].

Now: VCs look for balanced teams that combine technical excellence with business acumen. Founders must verify not only their ability to innovate but also their capacity to execute efficiently and scale [6][8].

6. Scalability and Infrastructure

Then: Scalability was often assumed rather than rigorously evaluated. Startups could secure funding without proving their ability to handle large-scale operations or diverse use cases[9].

Now: Scalability is a critical factor in VC evaluations. Investors assess whether a startup's technology can handle expanding datasets, computational demands, and broader market applications without compromising quality or margins[6][9].

7. Focus on Real-World Applications

Then: Generalist AI solutions aiming to disrupt broad industries (e.g., "AI for healthcare") were standard pitches that attracted funding despite lacking specificity[1].

Now: Task-specific solutions addressing niche but critical problems are preferred. Startups targeting enterprise customers with tailored solutions—such as compliance tools for fintech or supply chain optimisation—stand out due to their clear value propositions and focused execution[3][6].

What challenges do specialised VC funds face when investing in AI startups?

Specialised venture capital (VC) funds face various challenges when investing in AI startups, originating from the unique dynamics of the AI industry and broader market trends. These challenges include overvaluation, market saturation, scalability issues, ethical concerns, and regulatory complexities.

1. Overvaluation and ROI Concerns

The excitement surrounding AI has led to inflated valuations for many startups, often detached from proven revenue or profit-generating capabilities. Early-stage companies sometimes secure funding based on potential rather than tangible results, creating unrealistic expectations for long-term returns. This can result in reduced exit values and extended holding periods for investors who struggle to match lofty valuations with actual ROI[1][2].

2. Market Saturation

The AI sector is increasingly crowded, with numerous startups competing in popular niches like generative AI and machine learning automation. This oversaturation dilutes market share, lengthens profitability timeframes, and lessens the strategic value of particular investments. Specialised VC funds may need to navigate this competitive landscape by focusing on startups with distinct competitive advantages, such as proprietary algorithms or access to niche markets[1][3].

3. Capital-Intensive Business Models

AI startups frequently need substantial upfront investment in computational infrastructure, data acquisition, and specialised talent, which is getting harder to access and is at a premium. For example, training large language models can consume up to 80% of early-stage funding. Additionally, high salaries for AI engineers—averaging $300,000 annually—add to operational costs. These capital-intensive needs can sap the typical VC model and lead to challenges in securing follow-on funding at favourable valuations[2][3].

4. Scalability Challenges

AI technologies do not scale as easily as traditional software solutions due to dependencies on infrastructure, data consistency, and workforce expertise. Startups may excel in research and development but flounder with commercial scalability when adapting technology to varied real-world applications. Specialised VCs must evaluate a startup's ability to scale effectively while managing integration complexities[1][3].

5. Ethical and Regulatory Risks

Legal and ethical issues are becoming critical factors in AI investments. Concerns about algorithmic bias, privacy violations, deepfake proliferation, and copyright compliance are growing as governments introduce stricter regulations worldwide. Navigating these evolving frameworks requires startups to develop robust governance structures and ethical oversight mechanisms—areas that can be costly and time-consuming[6][7].

6. Winner-Take-All Dynamics

The AI industry is increasingly dominated by a few large players like OpenAI and Anthropic, which capture most of the profits due to their scale and resources. This "winner-take-all" dynamic poses risks for smaller startups that struggle to compete against well-funded incumbents or rely on commoditised technologies like cloud computing and semiconductors[2][3].

7. Economic Headwinds

Broader economic trends also impact AI investments. Weak earnings have made businesses wary about deploying large-scale AI solutions, while rapid technological advancements create hesitation about the longevity of current innovations. These factors contribute to a challenging fundraising environment for AI startups[7].

Strategies to Mitigate Challenges

To address these challenges:

• Specialised VC funds are starting to diversify portfolios across underexplored sectors like renewable energy or edge computing[1][4].

• They emphasise rigorous due diligence on scalability potential and ethical compliance[3][6].

• Funds are shifting focus from pure innovation to practical applications with measurable outcomes[3][4].

What are the key factors driving the increase in VC investments in AI?

The rise in venture capital (VC) investments in artificial intelligence (AI) is driven by several key factors, reflecting AI technologies' transformative potential and widespread adoption across industries. Here are the primary drivers:

1. Economic Potential and Scalability

AI technologies offer exponential returns, making them highly attractive to investors. Startups working on foundational AI models or mission-critical applications—such as generative AI, industrial automation, and healthcare diagnostics—demonstrate scalability and global economic influence. For example, generative AI funding nearly doubled from $24 billion in 2023 to $45 billion in 2024, with projections indicating growth to $1.3 trillion over the next decade[18][19][20].

2. Industry Adoption Across Sectors

AI has become an embedded infrastructure in healthcare, finance, and logistics. For instance:

• Healthcare startups are leveraging AI for drug discovery and personalised medicine.

• Financial institutions are using AI for fraud detection and risk management.

• Supply chains are optimizing operations with predictive analytics[19][20][24].

This widespread adoption underscores AI's ability to solve complex problems, driving investor confidence.

3. Strategic Focus on Monetizable Applications

The investment landscape is moving from foundational infrastructure to monetising AI applications. VCs are increasingly backing companies that integrate AI into their business models to deliver tangible outcomes, such as vertical-specific workflows or enterprise solutions that reduce friction and enhance efficiency[21][24].

4. Mega-Deals and High-Valuation Startups

Record-breaking funding rounds for prominent AI firms like OpenAI and Shield AI highlight the trend of VCs supporting large-scale projects capable of redefining industries. In 2025, startups securing $100M+ deals are concentrated in sectors like defence, healthcare, and SaaS, which promise profitability and societal impact[18][23].

5. Regulatory Developments

Governments worldwide are introducing frameworks or guidelines to regulate AI technologies, addressing data privacy, algorithmic bias, and security risks. While this creates compliance challenges for startups, it also signals maturity in the sector, attracting disciplined investments from VCs who value sustainable growth over hype[19][20].

6. Resurgence of IPOs

The growing IPO appetite for AI companies is another driver of VC interest. Major players like Databricks and CoreWeave appear to be preparing public offerings in 2025, echoing strong growth prospects and favourable market conditions that fuel optimism around AI investments[20].

7. Concentration on Established Leaders

Capital is increasingly flowing to dominant firms in the AI space, such as OpenAI and Anduril. This focus on established leaders suggests that investors prioritise proven business models over speculative ventures while selectively backing smaller startups with unique value propositions[24].

Final Thoughts

Today's VC evaluation criteria reflect a more mature AI investment landscape where practicality, defensibility, and sustainability precede hype and innovation. Startups must demonstrate technical prowess, ethical governance (adherence to ethical principles in AI development and deployment), scalable infrastructure, viable business models, and real-world impact to secure funding in 2025's competitive environment.

Specialised VC funds can navigate these challenges while capitalising on AI technologies' transformative potential by adopting disciplined investment strategies and aligning with sustainable business models.

These factors collectively explain why venture capitalists are doubling down on AI investments in 2025, recognising its transformative impact across industries and its potential to redefine economies globally.

References and Further Reading

[1] How DeepSeek Rewrote the Rules Venture Capitalists - Labellerr https://www.labellerr.com/blog/how-deepseek-rewrote-the-rules-venture-capitalists/

[2] VC's Framework for Evaluating an AI Startup's Tech Stack. | Sahil S https://www.linkedin.com/posts/sahilsr_vcs-framework-for-evaluating-an-ai-startups-activity-7274323044788035584-PhEF?_bhlid=16dc74d93eafa44bcfb9d58754a0e67a608d3257

[3] How to Be Investable AI Startup in 2025 - by Stepan Ikaev https://thecreatorsai.com/p/how-to-be-investable-ai-startup-in

[4] The 7 Secret Evaluation Criteria Venture Capitalists Use To Make ... https://thevcfactory.com/7-secret-evaluation-criteria/

[5] How VCs Evaluate AI Startups: The Frameworks You Need to Know https://www.linkedin.com/pulse/how-vcs-evaluate-ai-startups-frameworks-you-need-know-asthana-kzu5e

[6] AI-First vs. AI-Enabled Investment Framework - LinkedIn https://www.linkedin.com/pulse/ai-first-vs-ai-enabled-investment-framework-serhat-pala-7tewc

[7] What VC Investments Look Like in 2025 - Information Week https://www.informationweek.com/it-leadership/what-vc-investments-look-like-in-2025

[8] The State of the Funding Market for AI Companies: A 2024 - Mintz https://www.mintz.com/insights-center/viewpoints/2166/2025-03-10-state-funding-market-ai-companies-2024-2025-outlook

[9] Decoding The Evaluation Process Of Generative AI Companies By ... https://www.forbes.com/sites/josipamajic/2024/01/03/decoding-the-evaluation-process-of-generative-ai-companies-by-venture-capitalists/

[10] How to Invest in an AI Startup: What You Need to Know - Sembly AI https://www.sembly.ai/blog/investing-in-an-ai-startup/

[11] AI and Venture Capital: Redefining Investment Strategies in 2025 https://www.mahdlo.net/blog/ai-venture-capital-innovation

[12] [PDF] Navigating AI Investment Risks and Opportunities in Venture Capital https://meketa.com/wp-content/uploads/2024/11/MEKETA_Navigating-AI-Investment-Risks-and-Opportunities-in-Venture-Capital.pdf

[13] https://www.labellerr.com/blog/how-deepseek-rewrote-the-rules-venture-capitalists/

[14] A Reality Check for AI-Focused VCs: Deepseek's Disruption - LinkedIn https://www.linkedin.com/pulse/reality-check-ai-focused-vcs-deepseeks-disruption-taghashio-8gvbf

[15] AI craze getting funded by tech giants, distorting traditional VCs https://www.cnbc.com/2024/09/06/ai-craze-getting-funded-by-tech-giants-distorting-traditional-vcs.html

[16] AI investments in 2025: strategies VCs are using to navigate industry ... https://www.vestbee.com/blog/articles/ai-investments-in-2025-strategies-v-cs-are-using-to-navigate-industry-shifts

[17] Decoding AI Investment: Trends, Challenges, and Opportunities https://www.k4northwest.com/articles/decoding-ai-investment-trends-challenges-and-opportunities

[18] AI and Venture Capital: Redefining Investment Strategies in 2025 https://www.mahdlo.net/blog/ai-venture-capital-innovation

[19] The State of the Funding Market for AI Companies: A 2024 - Mintz https://www.mintz.com/insights-center/viewpoints/2166/2025-03-10-state-funding-market-ai-companies-2024-2025-outlook

[20] AI Investment Trends 2025: VC Funding, IPOs, and Regulatory Chall…https://natlawreview.com/article/state-funding-market-ai-companies-2024-2025-outlook

[21] Here are the types of AI companies enterprise VCs want to back in ... https://techcrunch.com/2025/01/20/here-are-the-types-of-ai-companies-enterprise-vcs-want-to-back-in-2025/

[22] What VC Investments Look Like in 2025 - Information Week https://www.informationweek.com/it-leadership/what-vc-investments-look-like-in-2025

[23] Venture Capital In 2025: Navigating The AI Hype And A Two-Speed ... https://gunungcapital.com/venture-capital-in-2025-navigating-the-ai-hype-and-a-two-speed-world/

[24] The AI Supercycle™ Report: Key Trends for AI Investors - VistaShares https://www.vistashares.com/the-ai-supercycle-report-key-trends-for-ai-investors-2/

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