The new reality of AI in investment

Across private equity and venture capital, a clear consensus is forming: AI is set to transform how funds source, evaluate, and grow investments, but only if it’s built around people, not just data.

Analysts from BCG, Bain, Gartner, and Deloitte all point to the same challenge: while generative AI can supercharge insight and efficiency, as many as 95% of AI initiatives still fail to deliver measurable ROI. The reason isn’t the technology; it’s the age-old problem of a lack of human alignment.

Firms that win with AI will be those that:

• Combine machine intelligence with human expertise.

• Train models on proprietary data rather than generic data sets.

• Take a CX and EX-led approach, identifying & framing the human problems to be solved and embedding AI within real workflows, not as a bolt-on experiment.
  
  

Where Raven started: Customer Experience and Employee Experience first

At Raven, that principle is in our DNA.

We began not as a tech company, but as Customer Experience (CX) and Employee Experience (EX) specialists. Our team spent years helping organisations design systems that actually work for the people who use them.

That heritage drives everything we do today.

Rather than building AI in isolation, we’ve built an Agentic AI platform that’s engineered around how investors think, decide, and create value.

At Raven, we’re CX and EX specialists first, so we’ve built AI that actually lands.

The result: faster dealflow, sharper diligence, and measurable portfolio growth for some of the some of the biggest and most successful companies on the planet from Amazon and TikTok to Dominos to Expedia.

A human-centred model for AI performance

Where many firms are still experimenting, Raven is already delivering the model analysts describe as the next frontier:

AI + expert orchestration that accelerates insight without losing human judgement.

1. Proprietary intelligence + data advantage

Raven enables firms to build secure, private large language models (LLMs) trained on their own deal history, portfolio data, and institutional knowledge.

This transforms unstructured information into a strategic asset giving investors analysis that’s not only faster, but aligned with their unique investment thesis.

In one case, a European PE fund used Raven to outperform a Big 3 consultancy on a €1bn transaction, achieving deeper insight, at a fraction of the cost and time.

2. Expert-layered workflows: humans at the centre

Research from Harvard Business Review and Bain shows that successful AI systems maintain a “human-in-the-loop” structure. Raven operationalises that principle.

Our curated expert network — The Ravens — includes world-class operators, sector specialists, and transformation leaders who interpret, validate, and refine AI-driven insights.

• AI generates data synthesis, benchmarks, and hypotheses at speed.

• Experts stress-test assumptions, inject context, and turn outputs into strategy.

This combination transforms AI from a black box into a precision tool, amplifying human judgement rather than replacing it.

3. Full-lifecycle transformation: dealflow → diligence → value creation

While most AI discussions focus on pre-deal diligence, Raven’s model extends across the full investment lifecycle:

• Dealflow triage: AI filters hundreds of inbound opportunities per week, aligned to a fund’s thesis.

• Due diligence: bespoke expert teams deliver targeted, rapid validation and market insights.

• Value creation: AI frameworks and expert input drive growth through digital, customer, and operational strategies.

Because the same intelligence engine runs end-to-end, every insight compounds, accelerating both decisions and results.

Why it matters for investors

For investment directors and operations leaders, the implications are clear: the future of diligence and value creation is already here and it’s hybrid.

Raven’s human-centred AI model delivers what strategy houses predict but few can operationalise:

• Speed — compressing diligence cycles from weeks to days.

• Depth — surfacing non-obvious insights through human-validated AI synthesis.

• Efficiency — delivering consulting-grade analysis at a fraction of traditional cost.

• Scalability — enabling institutional knowledge to live inside a private, secure LLM.

• Growth — extending beyond diligence into measurable portfolio performance.
  
  
  

Key takeaways

1. 95% of AI initiatives fail because they ignore human experience, Raven succeeds because it was built around it.

2. The future of diligence and value creation is not purely digital; it’s human + machine.

3. Firms that move now, building proprietary models and expert-anchored workflows,  will gain lasting competitive advantage.

4. Raven offers that model today: AI precision, human intelligence, and results that land.
   
   
   

Final thought

AI won’t replace investors, but investors who harness AI and human expertise will outperform everyone else.

Raven’s origins in CX and EX mean it’s engineered to make AI usable, understandable, and effective.

That’s why leading funds are already using Raven to move from hype to impact, achieving faster dealflow, sharper diligence, and measurable portfolio growth.

If you want to find out more and get a demo get in touch with via your preferred channel below.