The House of AI
Over the past 6 years, I’ve created and facilitated a well-reviewed B2B workshop on pitching and presenting innovative ideas and capabilities with a cross-disciplinary team. The soft-skills I include are based on a bit of my own experience, but mostly, they are skills supported by research.
Early on, my workshop was picked up by the Association of National Advertisers (ANA) as a perk/service for membership (a membership representing 20,000 brands). From the ANA, I learned how a large trade organization mandates the presentation structure (developed over decades) of what it offers paying corporate members, at every step of the process, in roughly 10-minute intervals over 3 hours. It was eye-opening and invaluable.
In 2020, I pitched the Harvard Business Review an idea to survey its readership about what the decision-makers in pitches and presentations want more (or less) of in pitches to them. And I would then write a second article with the results. 1,800 readers responded. The results were fascinating (to me), not only the insights, but also the passion of the comments. And as I had learned the ANA’s time-tested, best-practice, micro-view structure for holding a corporate audience’s attention through a 3-hour talk, I learned from HBR that by asking questions, I could build a solid foundation of insights from the answers of nearly 2,000 qualified decision-makers, rather than rely solely on own experience.
Today, I’ve been immersed in AI strategy for over a year. Thankfully, I am beginning to receive requests for talks on “AI literacy” – in the EU, a legal requirement for anyone working with AI, but in the US, more of a an overview akin to turning on the lights in the “House of AI”, only to discover just how many rooms there are – with more and more “rooms” (like Agentic AI) being added every day.
But let’s not get ahead of ourselves. I am trying an experiment: To give an overview of AI for businesses, I will borrow from what I have learned from my own experience with decision-makers, from my research, from the ANA and HBR. It will loosely be based on the metaphor of the House of AI, which will have about 9 “rooms” to peek into as we walk past.
The purpose of the experiment is to link the many narratives of the AI story for people who already know a few of the rooms, may even live in one or two as engineers or product managers – and hopefully, will contribute what they have seen, or point out what I have missed. Also, pacing matters. I have to confirm in roughly 10-minute intervals that the audience knows the answer to: “Why does this matter to my organization?” As in my pitch workshops, the goal is not only to educate about AI, it is also to provide a toolkit for exploring, building processes to reach a clear goal.
Over the next few posts, I will be describing each room in the House of AI, just enough to make it a story worth remembering – one that answers that calrifying question, “Who Cares?”
Chapter 1: I’ll See You There.
Everyone enters the House of AI through the front door open to them. An engineer will come in through a front door marked “Technology”. For an attorney, the front door is “Governance” or “Accountable AI”, for the Computer Scientist, that front door may read “Responsible AI”, etc.
And so the first room in an overview for business is “Understanding Where You Are” in the House of AI. What is the business problem to solve? What is the work/process to date? What has been learned so far, what to avoid, and what are the constraints? What does success look like? Who is involved (staff, vendors, etc.)? What is the timeline, budget, people, landmines, etc.
You will notice, I have a lot of questions. I have learned that questions are the lingua franca of AI, generally, and Business Transformation, specifically – that there are many experts in legacy predictive AI (especially in the Fortune 100 and other huge organizations), and there are many experts in areas tangential to much-newer generative AI, but very few who can provide an overview, much less a roadmap, for building and managing a successful Gen AI deployment for an organization, as Wharton’s Ethan Mollick points out.
Because if you are curious about AI, you are also standing on the diving board of Business Transformation. Prepare as much you can by asking questions, but don’t get stuck there. The outline from these next few posts are only a starting point – an initial organization of thought-starters that I’ll mold into shape with research, personal experience, and the ever-growing trove of expertise from an ecosystem of experts and use-cases.