AI and the Auto-Evolving Business: Part 3/4
My Conversation with Near Futurist Neil Redding
Welcome to Part 3 of our series on AI agents and agentic workflows. I’m excited to share my conversation with Near Futurist, Neil Redding. Neil is a keynote speaker, author, innovation architect and Founder of Redding Futures.
As a Near Futurist, Neil focuses on connecting the possible with the practical. He’s led innovation teams for Mediacom, Gensler, Thoughtworks, and with his own consultancy Redding Futures—leveraging the emerging possible in service of practical business value for his clients. And he’s a sought-after keynote speaker at events like SXSW, IAB, and Building the Future, as well as for corporate events at Microsoft, Meta, and others.
In this conversation Neil and I explore his concept of the “auto-evolving business” which envisions a new business model that leverages AI to adapt and evolve dynamically in response to changes in the external environment.
Whether you're a startup founder, a business leader, or simply curious about the future of AI, Neil's perspective challenges conventional thinking and offers a glimpse into the exciting possibilities ahead. Below is our edited conversation, highlighting key insights. For the complete, unedited video of our discussion, press play.
Emily:
Neil, I am excited to talk to you about how businesses are going to change in response to advances in agentic workflows. I’ve heard you use the term “auto-evolving business” to describe an emerging business model you see on the horizon as a result of AI developments. What is an auto-evolving business, and how did you develop this concept?
Neil:
The idea of the auto-evolving business is grounded in an idea I’ve been thinking and writing about for years; business models as ecosystems that evolve and update on their own.
The 20th century industrial revolution model of business is one of centralized management that requires design, implementation and building. Given how fast the future is arriving, that model is just no longer viable. You can't respond as a business, with all its manifestations and touch points with the world, quickly enough given the speed of change. And so for decades now there's been evolution in pockets of the industry.
Amazon is a great example. They've been very public about organizing their business in a decentralized way with a core set of operating principles. If you have a certain level of seniority you can spin up a new experimental product or service. As long as you define what success looks like in terms of metrics, and as long as it continues to prove out its value, it can keep going. This is how lots of new products and services happen inside big tech companies.
Moving beyond central management, planning and top down decision making — towards a decentralized approach is an important stepping stone to an auto-evolving business. The only way a business model could evolve on its own is by adapting to change. Similar to natural selection in the evolutionary model of biology, the idea of an auto-evolving business is that, at the touch points between a business and its operating context in the world, decisions can be made quickly in response to external changes—whether they're shifts in supply chain, pandemics or geopolitical movements.
The vision here is that AI and AI agents can, on their own, within the context of well defined principles of operating a business, respond at the speed of technology rather than the speed of human decision making, or committee based decision making. They can now respond to external changes much more quickly.
Emily:
Words like autonomous and decentralized probably sound a little scary to some business leaders. How does a company begin to move towards an AI enabled auto-evolving business model?
Neil:
I mentioned there are examples of companies like Amazon who have pioneered this shift from centralized top down decision making to more decision making at the edge. There's also been a lot of exploration by many different kinds of businesses asking how we make businesses such that the culture empowers distributed decision making, avoids the kind of bottlenecks that committee-based or executive-only decision making run into. There is a profound difference between the old school centralized decision making model of business versus a business that empowers people at lower levels in the hierarchy.
It can be scary for leaders to delegate. It’s scary hiring a new employee and allow them to make decisions. And I don't mean to suggest that AI is not potentially more scary than that, but I think it’s largely because we don't fully understand it yet—but we don't fully understand other humans all the time either. With technology there's the opportunity to solve for explainability. AI models explaining why they made certain decisions or how they arrived at certain conclusions is really important.
Then there's putting guardrails around them, right? To make sure that whenever they come up with some new strategy or decision, they can compare that decision or that strategic direction with guiding principles and, you know, raise a flag to escalate a decision to a human reviewer as needed.
And then the natural approach to all this is start small—start low risk.
Emily:
In addition to a culture that allows for decentralization decision-making, you mentioned the need for companies to clarify guiding operating principles in addition to their stated missions. Might adopting agentic technology force companies to align the two better?
Neil:
Absolutely, with this paradigm shift in technology there’s a need to clearly define and communicate operating principles amongst all participants, beyond stated purpose and mission. Defining guiding principles is a hugely valuable opportunity for companies, even aside from the need that AI agents will have for this principle-based guidance.
Emily:
Turning to the human question in all this; AI automation makes everybody very concerned about mass labor disruption. For individuals the basic question: is my job going away? What am I going to be doing in this new era? Is this going to mean opportunity - or its opposite?
Neil:
There was this post that went viral a number of weeks ago, in which someone said. “I want my AI to take out my trash and do my laundry, not the creative work that I actually want to do.” There's a societal realization that these aren’t necessarily the new capabilities we were looking for. For creatives, this is work that humans have been doing for a very long time and now seems threatened in some ways.
And yet those of us following the development of generative tools know that foundation models like ChatGPT or GPT-4, Gemini, et cetera, are trained on material that humans have already created. Though they can combine all of that material in new ways, can comment on it, correlate it, make inferences and analysis— they cannot do the real innovative and creative work by nature of their models - not yet.
And so humans are going to have to get better at doing that which is uniquely human. There's no question that generative AI will be disruptive to jobs— as it has been with every other disruptive technology-driven shift; whether it was industrial, manufacturing, transportation or digital.
[With the auto-evolving business] we’re now talking about a business model that has become possible over just the past few years thanks to generative AI, in the same way business models of today weren’t even conceivable 30 years ago, prior to the web.
In the next 3-5 years—what I would consider roughly the near future—we’re going to see new kinds of businesses becoming possible, and possible for very small numbers of people to create. As Sam Altman famously said a year or so ago, the one person billion dollar company is coming.
Among young people there's more entrepreneurial drive than I've ever seen in my lifetime. GenAI is going to dramatically accelerate what's possible for a very small team or even a single person to achieve.
As with every other shift, there are drawbacks, but I think the new possibilities that are accessible to just about anybody with an internet connection and twenty bucks a month for one of these models is so exciting that in some ways it compensates for some of that disruption.
It may take 5, 10, 15 years for a lot of legacy businesses to migrate to this new model of leveraging agents. As that happens I think we have to look out for each other at the level of society—in politics, government and business. Maybe we'll finally see some more serious experiments around universal basic income, for example, in order to make sure that people are supported as we transition to this new economy.
Emily:
That’s a great note to end our conversation today. Thank you for talking with me. I’m excited to see how your thinking on all this develops.
Neil:
Thank you, Emily. I look forward to keeping in touch. I love this series you've been creating in your newsletter to explore the impact from different business model perspectives.
To connect with Neil Redding and learn more about his work:
Tomorrow Mornings: Evolving With an Emergent World — join Neil’s breakfast series to prepare your business/brand for the agentic era