Refactoring organisations for the AI era.

Perhaps the most striking and shared excitement among leaders across many businesses is the top-line and bottom-line implications of AI.

This excitement stems from new and more effective ways of finding and converting customers and step-function improvements across top-of-funnel activities, through to completely refactoring various functions of the organisation to reduce cost.

In much the same way as the ubiquity of automobiles transformed commerce and society, the cost structure and overall efficiencies of most companies will change materially in the age of AI. Let’s discuss a few opportunities and tactics we need to be thinking about.

• The functional refactoring is upon us, and we need to lean in. I know a number of companies where CFOs, for example, have tasked leaders of every function within their finance organisation to come back with one way to refactor a critical and unreasonably burdensome or expensive part of their function. For example, procurement being reimagined leveraging an AI-first solution. I like the approach of charging every functional leader to do the research, run a trial, and discover one material refactoring project within 90 days.

• I want to use generative AI, now what? This is a common question I get. Great brands are eager to engage with this exciting technology but often debate how and where to get started. I propose a framework that is (conveniently) four P’s: Play, Pilot, Protect, and Provoke. PLAY – since novelty often precedes utility, you need to allow (with the right guardrails) your teams to play with this new technology (giving them access to ChatGPT or products like Firefly, but with rules). PILOT – pick one particular low-risk project and task your team with doing it “the new way.” This could mean leveraging GenAI for social media marketing images instead of the old way… whatever this means for you, identify a pilot project. PROTECT – your team needs to be allowed to fail when trying something new, so define an incubation zone of sorts for your team to do their play and run this first pilot. PROVOKE – as difficult questions emerge, foster an environment where they can be asked and debated. This is transformative technology with many ethical and meaningful implications that must be discussed.

• What the “AI will destroy jobs” pundits don’t understand: higher IPP (Ingenuity Per Person) leads to hiring more people: When speaking with groups of customers, journalists and industry analysts about the implications of AI, a common concern is job loss. Obviously, there are some things humans once did that machines will do for us – as always. However, what most people overlook is the natural persistent human drive to do more that extends to organisations, brands, and companies. If forced to choose between (1) launching and managing more products per employee, achieving more and better marketing in less time, covering more regions, and expecting more ingenuity per employee, OR (2) cutting expenses… what would you choose? Unless you’re a classic private equity shop disinterested in innovation and simply looking to squeeze pennies, everyone I know chooses #1. Perhaps this is why, after decades of engineers becoming more productive, companies keep wanting and hiring more engineers? My bet is that replacing mundane repetitive work with time for enterprising innovative work will ultimately increase the “Ingenuity Per Person” (IPP) that we get from employees. And once we do, we will want to hire MORE of these creative people. No doubt, we can expect slower expense growth, especially during the three year “great refactoring” period ahead of us, as AI solutions for every function come online. But this relative percentage expense cutting will result from better (or eliminated) processes, better speed, reduced error rates, and the growth of ingenuity and ultimately profitability.