How Artificial Intelligence Is Transforming Deal Sourcing and Startup Due Diligence

Startup investment is not like it once was. Those days are behind us when investors would be dependent upon gut feelings, spreadsheets, and meetings over cups of coffee to identify worthy founders. 

Now, artificial intelligence (AI) is revolutionizing how investors identify startups, evaluate them, and make their decisions. From automating the startup due diligence checklist to improving M&A strategy, AI is emerging as a significant helpmate to the process of deal-making.

As an investor who is looking to hone their edge, you should now take a look at how AI is changing the game.

The Old Method: Manual, Disorganized, and Time-Intensive

‍Let's start with a little flashback.

Deal sourcing was all about who you knew. You had to go where people are and be around people who are starting companies. You had to rely on referrals and let pitch decks fall into your lap or chase after them. Occasionally, you'd get a great opportunity from an unlikely source, but it was a time-consuming and shotgun process.

Next was startup due diligence: a deep examination of the company's team, traction, finances, legal status, and product-market fit. You'd analyze spreadsheets, scroll through LinkedIn profiles, and go back and forth via email with founders. Risky? Absolutely. Time-consuming? Indeed. Envision cutting that time by half or even further.

Enter AI: Your New Co-Investor

‍AI is no longer for coders and corporations alone. It’s entering the investment scene with tools that can assist you: 

• Get access to startups before they go big
• Rank and contrast investment options
• Run smarter and faster due diligence
• Make informed decisions based on data

Let’s breakdown how AI is transforming deal sourcing and due diligence for startups:

1. Deal Sourcing Is Supercharged

‍When there are startups everywhere, it can be like looking for a needle in a haystack to identify a good one. AI is transforming that by filtering through millions of data points across platforms—Crunchbase, AngelList, GitHub, LinkedIn, Twitter, news publications, and even pitch competitions—to bring you startups that fit your investment thesis.

Through natural language processing (NLP), AI tools are capable of interpreting your interests and suggesting startups based on factors such as:

• Market trends
• Founders’ backgrounds
• Growth indicators (social momentum, hiring surges, new rounds of funding)

Platforms such as SignalRank and Affinity monitor startup ecosystems and rank opportunities using machine learning algorithms that notify you when a new firm matches your thesis.

2. Quicker, Smarter Startup Due Diligence

‍Doing due diligence doesn’t have to be a chore. AI can now take over big pieces of the startup due diligence checklist, such as:

• Analyzing Financial Models
• Verifying founder backstories
• Reading legal documents
• Scanning the PR news or legal red flags
• Assesses competitors’ performance
  
  

It’s like having a virtual assistant who is always at work.

Imagine you are assessing a health-tech venture. AI can search through medical databases, news outlets, and patents and provide you with an overview of the regulatory scene, competitors in the market, and potential risks for the venture—all within minutes.

Platforms such as Zuva, Kira Systems, and Diligen are designed to derive insights from legal and financial documents based on machine learning. Others, such as Clearbit, automatically enrich company information saving you several hours of manual research. That is the power of AI for startup due diligence.

3. AI for M&A Process: Beyond Startups

‍AI is disrupting M&A as well. For investors engaging in acquisitions or mergers, AI assists you in finding target companies, conducting financial analysis, and anticipating post-deal consequences.

Suppose you are looking to acquire a smaller rival to enhance the market position of your portfolio company. AI can: 

• Analyze potential synergies
• Predict integration risks
• Assess cultural fit
• Predict post-merger performance 

This adds another layer of intelligence to your M&A strategy.

Example: AI-driven scenario modeling is employed by some companies to model how an acquisition would affect financials, customer turnover, or market share. Consider it chess for M&A, but based on data.

4. Leveling the Playing Field for Angel Investors

‍Traditionally, institutional investors held an edge. They had huge teams, access to insiders, and budgets for research. However, that's changing thanks to AI.

Today, single angels and small syndicates can access the same power of analytics that large companies employ for a fraction of the expense.

AI-driven CRMs help you manage deal flow. Tools for due diligence screen startups within minutes. Even term sheet analysis and negotiations can be done automatically. It allows you to go faster, and with greater confidence.

5. Personalized Investment Intelligence

‍AI learns about you over time too. It observes what kind of startups you're interested in and which deals you're not interested in. And then it personalizes future recommendations based upon those habits.

It's like having a Spotify for startup deals. For instance, if you invested in five women-led SaaS businesses, you'll begin to get presented with more such deals along with applicable data and risk levels. It's not just convenient that this type of personalization allows you to stay focused and goal-oriented.

6. Predictive Insights That Extend Beyond Pitch

‍Founders pitch visions, AI reveals patterns. By examining big datasets, AI is capable of identifying early warning flags or latent strengths that would not necessarily appear in a pitch deck. AI can monitor: 

• Team turnover trends
• Sentiment analysis of customer reviews
• Changes in web traffic or product usage
• Engineering activity or hiring velocity
  
  

In brief, AI uncovers what is behind the story. It enables you to pose improved questions, identify blind spots, and eventually make better-informed decisions.

7. Reducing Bias, Enhancing Objectivity

‍We all possess unconscious biases. Whether it be about a founder's school, accent, or pitch style, it can influence judgments. That can be done by AI.

By ranking startups against structured criteria, not gut checks, it brings objectivity to the assessment process. You get to make the final decision, but now it’s informed by clean, consistent data.

Of course, AI is imperfect. It can be biased by training data. That is why human judgment remains critical. However, when applied wisely, AI levels the field.

8. Challenges to Look Out For

‍AI is not a silver bullet. It has limitations, like any other tool. Some risks to watch out for:

• Overdependence on automation: Don’t overlook the human touch. The best founder dialogue is still important.
  
  
• Data quality: Bad data produces poor insights. Always double-check key information.
  
  
• Transparency: Certain AI systems are black boxes. Be aware of what assumptions the system is making.
  
  

Moreover, not every startup creates a digital footprint. Some early gems go unnoticed. So don't abandon your network.

9. Constructing an AI-Powered Workflow

‍Would you implement AI into your investment strategy? Begin small. Here's a straightforward playbook: 

• Choose a search tool like SignalRank or Crunchbase Pro to unearth startups.
• Track interactions and follow-ups using a CRM such as Affinity.
• Automate due diligence using tools such as Diligen (legal), Clearbit (data), or DocuSign Insight.
• Evaluate AI reports, but corroborate from founder calls and expert opinions.
• Update your startup due diligence checklist to address both human and AI checks
  
  

This hybrid approach allows you to be flexible and up-to-date.

10. The Future of AI for M&A and Startups

‍In the future, the contribution of AI for M&A process and startup space will continue to rise. 

We are heading towards predictive M&A with AI not just generating target suggestions, but even predicting outcomes from thousands of past deals. Venture firms already employ AI to model scenarios for fund performance and portfolio risk.

AI could soon even match founders with investors who are likely to fund them, based not just on previous behavior, but also speed of deals and areas of interest. Think of it as AI matchmaking for deal flow.

As new information comes available and machines become more intelligent, the job of an investor won’t go away. You'll spend less time searching, and spend more time thinking.

11.  Identifying Issues Even Before They Arise

‍Startups are inherently risky investments. However, suppose you could identify red flags early. 

AI is now being employed to identify latent dangers. Such concerns are founder conflicts, IP lawsuits, impending litigation, or irregular burn levels. AI can warn investors about potential danger by scraping public filing information, social media, ratings and reviews websites, and even court records.

For instance, a company might appear great on paper. However, AI could bring to light a dip in customer sentiment, an increase in Glassdoor complaints, or a founder's history of failed businesses. Such red flags allow further investigation or exit.

As you go through your startup due diligence checklist, using AI for risk assessment can shield your capital. It doesn’t replace instincts, but it refines them based on data. That's a big plus in a risky investment.

12. Real-Time Monitoring Once the Check Clears

‍Startup investment doesn’t go beyond the check. That is when hard work comes into action.
AI can benefit post-investment as well with real-time insight into how your portfolio businesses are doing.

Software can monitor web traffic, app store ratings, hiring activity, customer sentiments, and social buzz. You can even receive notifications for important milestones such as new fundraising, leadership shifts, or new product launches.

This transforms you from a reactive investor to a proactive business partner. If you notice a lagging engagement or a reduction in hiring, you can intervene early and provide help.

It’s a game-changer for fund managers or syndicate leads. With bandwidth limitations, it’s difficult to keep tabs on multiple businesses. AI enables you to observe all your investments without overwhelming you with dashboards.

Ultimately, all of these contribute to you managing risk, identifying follow-on opportunities, and bringing value with no permanent advisor team. It's an evolved way of startup tracking. 

Conclusion: Learn to Invest Smarter with Angel School

‍The investing future is AI-powered, not AI-displaced. To get ahead, you must know how to best harness these tools. That's not about merely installing computer programs, but mastering the tactics of savvy investing. We give you that knowledge at Angel School.

Our Venture Fundamentals program familiarizes you with all the basics of angel investment, including due diligence for startups and optimizing your M&A strategy. Whether you are new to investing or wish to take your game to a new level, Venture Fundamentals enables you to invest with greater confidence, clarity, and conviction.