Can companies use AI to become a better version of themselves? Able to act in ways they couldn’t act before? And if so, where would they begin? One place to look is outside company walls, in how everyday people use AI.
Many people who use AI use it for self-help, to free themselves from self-limiting behaviors so they can realize more of their potential. But everyday people do not have a monopoly on self-limiting behaviors. Companies also act in ways that blind them to possibility and prevent them from adapting to changes in the external market.
And yet it’s rarer for companies to use AI for self-help. Much more common are automation and workflow redesign. Both of these focus on known processes that we can improve. Self-help focuses on behaviors that get in our way.
Consider three examples:
The company wants to be customer-first, but describes its market in the language of its products. They routinely miss customer innovations that emerge outside their solution set.
The company wants to grow tomorrow’s customers, but focuses on protecting today’s leaders. Their pipeline of future growth prospects runs dry.
The company wants to drive experimentation, but discourages initiatives that may lead to failure. They regularly lose business that more agile competitors win.
We’ve all experienced these (and similar) dysfunctions at work. We often accept them as the cost of working in complex organizations. There’s no shortage of efforts to diagnose and address these dysfunctions, including company offsites, leadership principles, best-selling books, coaches and consultants.
What’s different now is the potential for AI to reinforce self-limiting company behaviors. Companies that automate and redesign workflows without auditing their behaviors risk giving renewed life to the assumptions that blind them to growth and change.
The company that struggles to be more customer-centric builds AI-powered product insights that paint a minutely detailed picture of existing customer behavior. The new dashboards draw even more attention away from the off-product customer behavior reshaping their category.
The company that struggles to grow tomorrow’s customers builds AI-growth scoring tools to shape account prioritization and investment. The tool naturally favors larger customers with more data, discounting emerging customers with thinner data.
The company that struggles to foster experimentation deploys AI compliance agents that track and anticipate out-of-bounds employee activity around the clock. Employees shift more time toward complying with today’s guidelines than exploring new, market-expanding ideas.
In each instance AI reinforces behaviors that prevent the company from seeing opportunity and adapting to a changing market. But this is not the only way to use AI.
Companies can also use AI like everyday people do, to replace self-limiting behaviors with new scripts that guide them to realize their potential.
For example:
The person who routinely misunderstands his partner may share a recent argument and ask the AI to “show me what I’m missing, help me see it from the other side.”
The person who can’t imagine herself in a new career may ask AI to help her inventory her skills and show her all the other ways to utilize them in adjacent and far-away careers.
The person trying to break a negative habit may ask for a detailed program for a healthier habit to try in its place together with an accountability plan to make it stick.
Companies can use AI to write new scripts that help move them past their dysfunctions, as well.
We don’t see our customers, we see our products. Help us see what we’re missing. Write scripts that push our sales team to capture non-product and non-customer feedback. For quarterly customer feedback sessions where product teams cannot defend existing roadmaps. For QBRs that begin with customer insight before sales and product performance.
We can’t imagine that today’s small customers could be tomorrow’s leaders. We measure all accounts by the same standard. Analyze our full customer set and tier them not by what they spend on us, but how their own business grows. Write a script for global account reviews that prioritize investment in the common needs of customers with the fastest growing business models.
We discourage experimentation that might lead to failure. We never question the risks of inaction. Identify opportunities worth pursuing from team communications. Write scripts for quarterly reviews that turn these opportunities into low-cost experiments and track what teams learn, regardless of outcome.
These interventions subordinate workflow redesign to the bigger challenge of correcting organizational dysfunction. We start by auditing the behaviors holding the company back, and implement new workflows that enable the desired new behavior.
Companies of all sizes have tried these sorts of interventions in the past. Some succeed, some fail. Those that fail often find it hard to sustain the change that’s needed over time.
The energy from the offsite fades after a few weeks. The excitement over new leadership principles lasts a quarter or two until something more pressing takes over. Best-selling books and their checklists age. Coaches and consultants come and go.
But AI can be on, always. It’s there before and after the offsite, once the leadership principles have been cascaded, when the book’s back on the shelf, and when the coaches and consultants have moved on. AI persistence helps teams maintain the momentum needed to turn dysfunction into function.
It also inverts the relationship between people and AI. When we use AI to transform or automate workflows, AI takes on aspects of our work and we monitor the progress and outcomes. When we use AI to help correct self-limiting behaviors, we do the work and AI monitors our progress and outcomes.
The first bets that by AI taking on more work, our people will have more free time to devote to new initiatives. The second bets that by overcoming self-limiting behaviors, our organization will expand the boundaries of what it can do.
Ultimately, companies will need both to maximize their AI efforts. They will need to find efficiencies and increase productivity to keep up with competitors. And they will need to overcome their self-limiting behaviors to serve more of the market.
We are a few years into the first journey. But only at the beginning of the second. Motivated teams can take inspiration from how everyday people use AI to become better versions of themselves, and write a new script.