What Great Companies Will Get Right Next
April 9, 2026
Today I was reading unconnected articles on HBR and started spotting a few patterns across them. Which got me thinking about great companies of the future.
Managers & Executives Disagree on AI and It’s Costing Them
Leaders and middle managers aren’t on the same page when it comes to AI. They hold fundamentally different views on whether AI is delivering ROI, how quickly their organisations are adopting AI, and how the technology may impact their teams and skills.
Of the five concrete actions it recommends leaders to take to address this, one stood out.
Measure readiness, not just adoption - the article recommends that manager confidence and organisational readiness should be explicit KPIs alongside usage metrics. It’s telling that 76% of executive leaders believe their employees feel enthusiastic about AI adoption, 51% of middle managers do whereas only 31% of individual contributors say they are.
This connects to MHA recently making AI usage a key metric for pay and progression. Brute forcing adoption could expedite innovation whilst simultaneously turning a blind-eye to the cultural and human day-to-day realities of the middle managers and individual contributors. Great companies of the future will start to lean into the operational realities with empathy and set aside more change budget. After all, 70% of the value is in rethinking the people component.
Why Gen AI Feels So Threatening to Workers
Mark Zuckerberg said last year that Gen AI makes it possible for motivated workers to “accomplish way more than they ever could before.” Leaders agree, in a survey of senior decision-makers at large U.S. companies 89% of respondents say that gen AI enhances employees’ skills.
However, in the same survey, 71% said that they believe gen AI will lead to the atrophy of employee skills.
I see a huge opportunity for organisations to help their people explore and understand this through a lens such as Gallup Clifton Strengths. It’s a ranked list of 34 human attributes. Great companies of the future can take the individual as the starting point for re-thinking job roles and workflows. Simply put, what are the superpowers of that person that might be turbocharged and where might skills atrophy matter less. This is an evidence based and thoughtful organisational redesign with a clear downstream business case in retention and productivity.
If the workplace is redesigned forensically bottom-up in this way, it’s logical that the implications of this in other areas of the business (e.g. hiring and upskilling) will be quite profound. It also reveals both to the individuals and the leaders what the emerging DNA of the future organisation is. For simplicity this can be thought of across the four Gallup domains - strategic thinking, relationship building, influencing & executing. It may have the positive unintended consequence of helping leadership teams to revisit their strategy and battle plans.
I call this Human-First AI transformation.
Research: Using AI Can Stifle Innovation. But It Doesn’t Have To.
At Faculty we talked a lot about First Principles thinking.
In the GenAI era, a plausible strategy memo appears in minutes, fewer people will spend days doing the harder work that produces original understanding, such as talking to customers, triangulating data, and pressure-testing assumptions.
This article refers to an organisation's Absorptive Capacity: the ability to evaluate, adapt, and improve ideas rather than just copy them. When people must invest some effort to use what others found, they do more independent checking and tinkering.
This is a warning to leaders as to how carefully and thoughtfully they introduce innovation into their business. If everything is built on quicksand then first principles are nowhere to be seen. Through the brute force approach, perhaps people become unknowingly transformed into information retrievers. In this future scenario there becomes a dangerous explainability vacuum.
Without Absorptive Capacity then the culture is one of ‘good enough’ solutions. Interestingly, in an era where no organisation is exempt from re-thinking workflows or job roles, a firm lacking absorptive capacity is likely to ask LLMs and Agents to redesign the organisation for them. Whilst this approach could be fantastic for ideation, if leaned on too heavily it would actually create a non-novel, likely to be commoditised new business.
Great companies of the future will need to introduce Strategic Friction. Too little friction undermines exploration. Too much slows everything down. And not every task warrants friction. Strategic friction should be reserved for the tasks where the organisation needs people to think and learn, not just produce. Strategic friction is the Goldilocks zone - 70mph on the motorway. These organisations will reach new destinations before others (in innovation parlance known as Blue Ocean Strategy).
When Silos Hinder Innovation and When they Help
In an analysis of 294 empirical studies on collective innovation, it was found that connecting people to collaborate doesn’t have a consistent effect on innovation outcomes. Sometimes it’s strongly positive. Sometimes it’s negative. Sometimes it has no effect at all.
So the conventional wisdom to break down silos - hiring good collaborators and applying them everywhere - is exactly what the article is warning against. Innovation emerges under different conditions depending on how collectives are structured, how members interact, and how aligned their goals are.
Again, consider Gallup Clifton Strengths. Great companies of the future will recognise that the structure of the collective is the differentiator.
Convergence-Based Collectives: When innovation problems require tight integration of expertise, convergence-based collectives bring the right people into the same room, literally or virtually, to solve problems together. This work requires constant integration of ideas, fast decision convergence, heavy cross-functional dialogue.
Divergence-Based Collectives: Sometimes the best innovation comes from multiple entities pursuing their own paths within a shared ecosystem. This work requires maximum variation, minimal coordination cost, optional collaboration.
Attention-Based Collectives: For well-defined problems where multiple solution paths are possible, attention-based collectives harness independent work at scale. The work requires the same problem, parallel independent exploration, protection from early consensus.
The biggest hidden risk is over-indexing on relationship building across all teams. This feels culturally good but systematically reduces innovation variance.
Leaders should think about which talent profiles thrive in each structure. Then test combinations of these. This touches on my previous blog about the advantage of uniquely configured humans. In the AI era cognition becomes abundant but human to human interaction becomes the bottleneck. Execution and strategic thinking is turbocharged, influencing and relationship building feels clunkier.
This is therefore a design choice for leaders.
At CHAPTR we discussed a new type of software that grows/adapts with the individual and team as they collaborate and pursue growth / innovation. This section reminds me of this. That’s a unicorn level problem if a team cracks that.