How to embrace AI before it disrupts your business
Having already articulated why legacy businesses, post-2008, have struggled to reclaim significant growth and productivity. In this article, and building on my commentary in HR Magazine, I wanted to offer some practical solutions for managers by using a recent partnership case study to capture the potential new capabilities managers will need going forward, as they are critically important in meeting the AI transformation.
Topline message: The bad news for managers is that organisations will need fewer managers, but the good news is they will be more empowered and better paid.
Firstly, how did we lose such an integral and vital capability in our large organisations?
In the effort to deliver growth, post-2008, in an epoch of near-free money and a way of integrating global, multi-market reach, leaders followed a growth playbook - M&A, restructuring and digitisation of their business. Applying matrix, agile and digitally empowered integrated business models. They rolled out organisational efficiencies, including outsourcing, offshoring, and streamlining. They aggressively flattened their structures, as they removed middle management layers and costs - “fast” became more important than structured process capabilities that worked.
Additionally, encouraged by the strat-houses, leaders prioritised strategy over management and business transformation capabilities, conveniently passing responsibility for delivery to the people function, who were often under-supported and under-resourced. Culture became performative and disconnected from performance, represented by three descriptive words on the foyer wall, rather than capability-driven.
Through this process, organisations inadvertently eroded their management capabilities and weakened the organisational alignment thread, undermining the ability of all their people to contribute successfully.
The irony is that AI demands high-capability AI-enabled managers.
The Brief: A global client wanted to drive significant cost reductions and efficiencies through removing management layers, unproductive and distracting activities, as well as underperformance, whilst simultaneously transitioning to a high-performance AI-enabled, external-looking culture, spearheaded with new assets which targeted new customer segments in new ways.
Although this sounds like a lot, this is the most common brief we receive now. We helped their leaders focus on the management layers and capabilities.
According to Gartner, by 2026, 20% of organisations will leverage AI to eliminate more than half (you read that right - half!) of their current middle management roles. A recent Korn Ferry Workforce survey underscores this shift, with 41% of employees reporting that their companies have already reduced managerial layers. A new Gallup survey finds that managers are experiencing the sharpest decline in engagement.
This apparent dichotomy of organisational direction points to the reality that the generalist, “legacy thinking” manager will be removed, to be replaced by the new and prioritised AI-enabled manager.
However, the impact of losing management layers can quickly lead to employee confusion, dissatisfaction, and disengagement, but also potentially create further organisational dis or misalignment, weakening cultural know-how, management capabilities, and cohesion and loyalty.
Korn Ferry survey also stated that 43% of employees say their leaders aren't aligned, and 37% say the lack of managers has left them “feeling directionless”.
The potential risk for legacy businesses is that if they don’t deliver on the AI management transition effectively, they may find that it stops the AI transition in its tracks, making the leap to becoming an effective AI-enabled business impossible.
We’ve all read about the potential of the AI “white-collar massacre”, and yet the temptation for efficiency gains by automating many traditional middle management functions will be tempting and obvious, as the pressure to deliver, given the sunk costs in AI, is real, and leaders will be looking for the easiest and most obvious quick-wins.
But leaders need to be cautious about ripping out yet more middle management. I have already written on the cost of tearing out all that mid-management culture and organisational knowledge; they know all the shortcuts and buried operational skeletons. They know all the obscure workaround patches for all the disjointed, layered-up tech purchases that are held together with metaphorical digital string. But if you lose your managers, you also break up the traditional career ladder pathways. After all, leaders were once managers too.
We have all seen and felt business performance transformations that have not been led by a clear and compelling purpose, vision and narrative. Without that sense of an inspiring direction, colleagues will struggle to get on board.
At the heart of that organisational transformation is the manager.
A good manager can make or break departments just as good managers can make or break business performance and business transformations. They coordinate teams, oversee operations, and ensure accountability - they turn the organisational cogs. But of course, this is where AI efficiencies will bite first.
Remember, automation alone doesn’t guarantee successful business transformation or future performance.
We encouraged the client to focus on their best and most capable digitally savvy middle management talent, and support their accelerated importance and impact in the business.
The rise of the AI-manager might cause some blurring of roles and functions, but those that flourish will become tomorrow's AI-enabled departmental, divisional and executive leaders.
We asked the leaders to select their best, most digitally capable managers, who also demonstrated commercial and performance capabilities. And then we got them to deliver on an AI gamification experiment - unlock a real and current opportunity or challenge with AI.
Observe what comes back - recognise and reward success based on the greatest potential scalable impact through their new insights, customer-centricity, application, efficiencies, whilst navigating contextual realities and current commercial drivers.
Those who delivered are likely to be the AI managers you want to keep and build the business around.
We helped them think about these AI managers in the following three ways:
As AI Agents and tools continue to evolve and develop apace, it becomes incumbent on AI managers to be the most AI knowledgeable person in their teams. In particular, they need to demonstrate and model the impact and use of AI within the performance framework of organisational context, commercial application and customer centricity.
They will need to have mastery over AI impact and management dashboards for their teams to avoid scope or activity creep, bottlenecks, inefficiencies and ensure they are aligning their teams' efforts, activities and contributions to the strategic growth agendas. This approach required strategic and AI capabilities alongside traditional people management skills. Remember, this is about the practical application of AI, not the bleeding edge of tech upgrades, or the dystopian future impact.
They will need to constantly roll up and roll down teams of AI-enabled colleagues. They will need to be able to orchestrate hybrid teams that have different experiences, capabilities and demands, who may be geographically dispersed and very diverse in their backgrounds, ages and experiences. The AI Manager will need to keep their teams focused and on point. The opportunities for distraction and atomisation of focus and resources are infinite.
We will see the rise of what we call the operational spider model. Where organisations keep the most expensive and capable talent centrally, then allocate them out to the locations and markets where they are required to deliver the greatest impact and efficiencies. Managers will be closer than anyone to the market, field or the customer, making managers critical to the business transformation. They are more likely to see the downstream impact of disruptions and headwinds before anyone in the business, and, therefore, most likely to design the evolving nature of AI to respond to those evolving realities.
AI Managers will act as the trainers, information sharers and coaches of their hybrid teams. Offering integration of AI and the evolution of daily new insights, disruptions, tech launches/upgrades or skills required. They will need to help their teams navigate the constant and accelerating change as AI upgrades deliver real-time impact and change. They will need technical skills but also human management skills to ensure everyone in their team keeps evolving and adapting without burning out.
This helped our client with a framework and to focus their most talented managers think about their new capabilities and skills that they would need to master as well as their evolving role and their AI change journey. It also helped unlock the contributions of ALL of their people.
Lastly, at the heart of our organisational transformation work, Arrival delivers a concept called Organisational and Contributory Alignment. Acting as a back-to-basics business fundamental, to ensure the business architecture is in place and aligned to the executive growth and business transformation agenda.
It also reestablishes the organisational alignment thread, ensuring executive message transmission is successful, and sustained organisational change traction occurs.
This alignment aspect is critical for legacy large-scale businesses, as without it, all their resource and change efforts will struggle to land and get performance traction. As has been the case post-2008.
At the heart of a successful AI business transformation is the new AI-Manager. Fewer of them, but more important and empowered. Vital to the success of this transition.
The costs of leaders not getting their AI transformation right are too great for them not to lean in and ensure this AI management capability journey. What is the point of costly AI tools and investments if the organisation doesn't have the capabilities or approach to using them effectively and with impact?
The window for making the leap to becoming an AI business is narrowing all the time.
