AI Challenge Part 2: How AV Incubates AI Applications
7 Takeaways (So Far) From Onboarding Revolutionary Tech
In this op-ed, I share my vision for AV to become the most AI-powered VC in the industry and highlight our firm’s progress so far. Venture Capital Journal published this piece on June 21, 2023.
If you missed part 1 of my op-ed, I cover why AI has the potential to be the most disruptive technology of all and how it can make a huge difference given the context of AV’s unique investing model. Faced with the challenge of how our company should approach AI, I explain why I chose to go “all-in.” Click here to read more.
After getting teammates acquainted with AI tech, we wanted to home in on very practical ways it could impact daily work. Our focusing mechanism was the creation and launch of AV’s AI Challenge. This contest split the company into teams — 43 in all — based on departments. The contest charged our people to come up with AI applications relevant to their jobs, workflows, and deliverables.
Expectations were clear. We laid out the scorecard (process 40%, results 40%, and presentation 20%) and a deadline. Carrots were prizes of cash or equity ($100,000+ in total), plus obviously seeing the best ideas backed and developed by AV resources. We made tech and consultants available to help, but largely left the teams to innovate independently. Critically, we walled off deep work time blocks for them to huddle, discover, and build.
Another key decision was to keep the bosses out of the way. This contest was to bubble up great ideas and automations from the field. We wanted to empower team members to discover and think, creating true ownership of solutions.
Why a contest with prizes?
- Dramatic signaling
- Distributed and practical
- Learning is often better in a peer-to-peer setting
- Fun and interesting
- Competitive juices
- Hard deadline on results
Alumni Ventures’ 2023 AI Challenge
How should a company introduce AI to its staff? At Alumni Ventures, we decided on an intense, company-wide initiative to rapidly educate and motivate our employees: AV’s AI Challenge, an internal competition to incubate the most effective AI applications. Click below to watch an overview of the challenge and how it worked.
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Six weeks later, the judging took place over three days. Each group had 10 minutes for their pitch. Judges were asked to hold questions until teams finished their presentations, then we privately scored and conferred. I made the intentional decision to watch every session.
The results: We found the ideas to be astounding in terms of variety, applicability, impact, and sheer cleverness. To my surprise, the floor was incredibly high — ranging from good to groundbreaking. A small sampling of those ideas — some proof of concept, some nearly complete — all leveraging AI:
- Customer Service: Automation that generates personalized, on-demand portfolio reports for all 10,000 customers, showing their investments, performance, and diversification.
- Legal: Automating 80% of the most time-consuming legal tasks, such as comparing term sheets to legal documents.
- Investing: Rapid identification and evaluation of rising venture professionals, enabling early partnering with attractive deal sources.
- Investing: Detection of ventures in the process of raising a round (usually a very private process) by spotting faint data signals in public communications.
- Sector Research: Efficient compilation of information on an emerging sector and prep of a white paper to quickly deliver rich, topical content in 1/20th of the time.
- Portfolio Monitoring: Monitoring, interpreting, and alerting investing teams on key changes at the 1,100+ companies in our portfolio.
Ultimately, we chose 20 winners from across the company and provided all teams with constructive feedback.
My 7 Takeaways (So Far)
Besides walking away with many impressive and actionable AI applications, the judges and I learned what worked about our approach.
Insights Into ProblemsUnderstanding the problem being addressed was as critical as solving it. Team members walked us through workflow diagrams, task mapping, and identification of roadblocks. This process not only gave the judges key insights but allowed team members to detach from daily operations and understand the bigger picture.
The Power of TeamsWorking in teams proved hugely beneficial. The challenge brought teams closer and allowed those lagging in AI adoption to bridge the gap. Teams inspired each other and found unity and pride joining with all employees in working on an innovative, challenging initiative.
Balancing Top-Down and Decentralized ApproachesOur combined top-down and decentralized approach was highly effective. While directives, vision, and resources were provided from the top, employees were empowered with the tools and autonomy to explore and innovate, encouraging ownership.
Framing Problems — and SolutionsWe suspected and confirmed that a one-size-fits-all approach wouldn‘t work for implementation. After the contest, we developed a tailored framework that evaluates the level of development and resources required for each idea, along with its potential impact. Our evaluation involves identifying problems that can be solved with ready-made solutions and others that require in-house development for proprietary advantages.
Significance of Corporate CommitmentWe walked the walk. A strong corporate commitment in terms of messaging, time, resources, and funding encouraged employee engagement and buy-in.
High Tech & High TouchWe learned that optimal solutions were both high-tech and high-touch. Most of this technology is not ready to be unsupervised, so our teams carefully considered human QA and “last eyes” processes. However, by automating routines or gaining new insights, we will free up time to think at higher levels and to do things that humans do best — like build relationships, connect far-flung ideas in novel ways, and lead.
Not Letting UpPost-challenge, we found it was essential to keep communicating regarding results, development plans, and implementation. In addition, continual information sharing about AI has helped engrain the technology into AV’s culture and our way of thinking.
We’re already deep into Phase 2: sorting through contest ideas, determining what teams can implement by themselves vs. what needs collaborative development, and priorities for our work. Our cross-departmental implementation team has been evaluating, bucketing, and prioritizing contest ideas, focusing on the highest-impact solutions first. We already see that developments on one solution can be applied to others, so we expect development to accelerate as we proceed.
Beyond development plans is our commitment to continue experimenting, sharing, and implementing AI. Undoubtedly the tech needs to improve in some areas, and challenges like bias, security, surveillance, and other issues loom. But this is the worst the tech will be…and it’s already amazing. Given AI’s stunning evolutionary pace, improvements are likely already on the horizon. Welcome news, and our company is now ready for the challenge.
Every great technology wave has been accompanied by handwringing and catastrophizing. But the net results of powerful new tools are generally positive. The AI genie is not going back into the bottle. For the sake of our society, company, customers, and teammates, AV plans to stay all-in on AI, making the best use of the tech.
About Alumni Ventures
Alumni Ventures offers accredited individuals access to professional-grade venture capital — a key asset class missing from the portfolios of many sophisticated investors. Since 2014, AV has raised more than $1.1 billion across 30+ Alumni and Focused Funds, serving a growing network of 9,000+ investors and 600,000+ community members. AV evaluates hundreds of investment opportunities every year and has backed 1,100+ unique portfolio companies. According to PitchBook, AV is the most active VC firm in the U.S. and the third most active firm globally. AV funds are private, for-profit, and not affiliated with or sanctioned by any school. For more information, visit av.vc.
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Our AI Fund will invest in a diversified portfolio of ~20-30 companies applying AI, machine learning, big data, and related technologies. The fund will be invested over ~12-18 months with a large reserve (~20-25%) for follow-on opportunities. AI Fund 2 was oversubscribed, and we had to establish a waitlist to accommodate interest. Click below to review fund materials or connect with a Senior Partner to learn more.