AI resistance isn’t where you expect it

After meeting customers and reviewing their feedback about our ignio products for nearly two years, I am now confident of two things: 

First, user resistance to adopting a new AI-driven solution is by far the biggest impediment to customer success, not AI technology challenges.  

And second, middle managers are one of, if not the, major resistance points to AI adoption. This is mainly because AI transformation threatens the middle management status quo. This blog will describe this major adoption blocker and what can be done about it. 

Transformational concerns are often focused on IT operations staff whose jobs AI will directly impact. However, IT experts are always in high demand. So even if their jobs end up being replaced by AI, they will quickly find an equivalent job (since information technology is a continuously growing sector).   

By contrast, middle management not only will struggle to find a suitable alternative, but also will struggle to adapt to new working environments.  

Status anxiety motivating managers

Middle managers are usually status-driven, gaining monetary and personal satisfaction primarily from their professional roles. Both salary and status are usually driven by the overall cost they manage (typically measured by department size) – not the value they create (for example improvements in  revenue, profitability, or customer satisfaction scores). 

Their role is also usually enforced by a command-and-control approach. Their teams are often reminded to execute more than to think. Many white-collar jobs (and IT is not immune) have been shaped by years of practical adaptations of Taylorism, a/k/a scientific management, which fundamentally break down jobs into small sets of repeatable and executable tasks.  

Such an approach is a huge advantage for AI adoption, as I mentioned in an earlier blog. But it has also created a huge impediment: All decision-making power is in the hands of middle management.  

AI means less blind repetition, more thinking

AI can replace human activities that do not require self-awareness. (AI as of now is not self-aware. It predicts and acts based on mathematical models, but does not understand the context where it operates.) This means AI will replace repetitive tasks, but it will require the labor force to be aware – to think.  

And that means AI is eroding the two fundamental principles that support the middle management role: 

• It eliminates the need for humans to blindly execute tasks. Smaller teams mean the size of middle management’s sphere of perceived influence will be reduced – along with their pay. 

• It requires humans to wake up and think. Staff will no longer just execute tasks. Instead they will continuously propose ideas and engage in discussions on how to improve business value. Management will be paid and judged by their ability to create value – and that will no longer depend on how well they make their staff follow orders, but how well they can unlock their teams’ higher-order skills.  

AI empowers staff and disempowers middle management. It promises to overcome the cynicism of the famous Pink Floyd lyric, “All in all, you’re just another brick in the wall.” Staff becomes the fundamental cornerstone of productivity. 

Management resistance in action

I see it every time I do a deep dive at customers both at the initial phase of a transformation or in the middle of it. For example, my team and I were presenting an ignio transformation proposal to a North American customer.  

Our proposal was flat-out rejected because we spent too much time describing what ignio is and how ignio uses AI to deliver IT operations, instead of describing how a traditional human-driven service would work. Middle managers did not want AI because they were  concerned that a machine-powered service would make their accurate and complicated support process obsolete. Middle management just wanted to stay on what they were comfortable with: an IT operation driven by command and control, taking advantage of the lower costs of an overseas workforce. 

More recently I was doing a deep dive into a case where the customer believed in the capabilities of ignio but was highly disappointed by its adoption. A detailed analysis found that  middle managers at the customer’s system integrator were stonewalling ignio transformation just to keep their status quo and what they were comfortable with. This line of thinking is common. 

Getting middle managers and AI on the same team

To solve this issue, I suggest the following three steps: 

• Acknowledge the problem. Middle management has been the linchpin of any business organization, and it is the product of decades of business evolution. Before embarking on any AI transformation, take the time to understand its impact on middle management. This will help you understand who the decision-makers should be and support middle management later. 

• Empathize with middle management transformation. Create a proper change management process where new roles are defined and management can transition into a new business environment where machines execute, and humans think! Above all, explain that middle management will be measured on value created, not headcount cost managed. 

• Periodically verify progress on how both ignio and middle management are transforming. Any transformation is a journey. Tracking progress and verifying how change is progressing is critical, especially where those transformed (middle management) are driving the transformation. 

As Astro Teller described it, we live in an era where our ability to innovate is greater than our ability to adapt. (This is especially true for business organizations.) The best and fastest adapters of innovation are the winners. AI is a mature solution with clear advantages. IT operations teams need to ask themselves, not: “How AI will adapt to my processes?” but “How will my IT processes adapt to AI?” 

In a future blog post, I will describe how Digitate is coping with its adoption journey. Yes, even a company that creates innovation has its challenges adopting innovations! 

To learn more about AI adoption issues within middle management and how this fast-growing technology will affect the overall shape of work in the digital enterprise, check out this recent episode of Recruiting Future with Matt Alder, featuring CCO Ugo Orsi and Jennifer Longworth, Director of People and Culture at Entuitive.  

Written by Digitate's CCO Ugo Orsi