Most AI projects fail not because of technology - but because of broken workflows and people not using it. We fix this by putting AI inside your existing tools, using behavioral science to get your team on board, and making sure your data is never stored by any public model.
Why AI Projects Fail
And How We Fix It.
Most AI projects in PE fail because people don't use them, not because the technology doesn't work. We build AI that fits into how your team already works, so they actually use it.
After deploying AI across 30+ PE, family office, and alternative investment engagements, we've learned that the difference between AI that transforms and AI that sits unused comes down to three principles.
By Dr. Leigh Coney, Founder of WorkWise Solutions
The Three Reasons AI Projects Fail
Four Steps to AI That Sticks
Every WorkWise engagement follows this sequence - from fitting into your tools through locking down your data.
The Friction That Kills AI Initiatives
We've seen it repeatedly: firms invest heavily in AI only to watch usage stall at 20%. The technology works. The business case is solid. But nobody thought about whether people would actually use it.
In the BCG/Mollick study, below-average performers benefited most from AI, seeing a 43% improvement in quality, while top performers saw only 17% improvement (Dell'Acqua et al., "Navigating the Jagged Technological Frontier," 2023). For PE: AI helps the team members who need it most - but only if they actually use it.
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Generic AI toolsThat don't understand how you make decisions. Off-the-shelf solutions treat every firm the same, ignoring the specific workflows your team actually uses.
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People not using itTeams see AI as disruption, not help. Senior professionals have refined their methods over decades - they won't abandon them for something that creates more work.
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Workflow disruptionThat creates more work instead of eliminating it. When AI requires learning new interfaces and changing established processes, adoption dies.
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Security concernsAbout proprietary data training public models. In high-stakes environments, the risk of competitive intelligence leakage is a non-starter.
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AI inside your existing toolsWe put AI into how your team already works - no new interfaces, no changes to their routine.
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Matches how you actually workWe study how your people make decisions before writing a single line of code.
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People actually use itWe use behavioral science to tackle the reasons people resist, so your AI investment actually pays off.
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Your Data Stays YoursYour data is never stored and never trains public models. You control your confidential deal flow, investment theses, and client engagements completely.
The Invisible AI Approach
The best AI disappears into the workflow. It doesn't require training. It simply makes your team better at what they already do.
Enhance, Don't Replace
We don't build AI to replace your people. We build AI that makes them faster. Your analysts, partners, and consultants have irreplaceable expertise - our job is to eliminate the grunt work that prevents them from using it.
Integrate Without Friction
The biggest reason people don't use AI is friction. That's why we put AI inside your existing tools - your email, your document systems, your workflows. No new platforms to learn. No changes to how you work.
Earn Trust Through Results
Skeptical senior professionals won't trust AI because you told them to. They'll trust it because it consistently delivers value. We design for early wins that build momentum and long-term credibility.
Where the WorkWise Approach Differs
The High-Stakes AI Blueprint
For PE firms, family offices, private credit, and independent sponsors, we've built a framework that combines data security (your data is never stored), financial ROI modeling, and a proven approach to getting your team to actually use what we build.
Andrew Ng, co-founder of Coursera and former head of Google Brain: "Most of the value had better be at the application layer." We put AI directly inside the tools PE teams already use every day.
From Principles to Production
Discovery Sprint
2-3 weeks to map your AI opportunities, validate feasibility, and produce a concrete action plan. $30K fixed fee, credits toward build.
Custom Build
Custom AI systems deployed within your infrastructure. From deal screening to portfolio monitoring, fixed scope, fixed price, MVP in 6-8 weeks.
Solutions We Build
8 AI systems built for investment professionals - covering Deal, Portfolio, Market, and Stakeholder Intelligence.
Embedded AI Partner
A retained AI partnership for continuous development. New capabilities in rolling sprints, strategic advisory, and priority build access.