Navigating Tensions in Digital Transformation: Managerial Action Across Levels
Companies rushing into cloud computing, AI and other digital tools often assume the biggest hurdle is picking the right technolog y. New research by Ayomide Peter Alao suggests the real challenge lie s elsewhere: in the everyday judgement calls made by middle managers, caught between defending what already works and chasing what might w ork better.
Established companies rarely have the luxu ry of starting from scratch, unlike digital-native rivals. They must keep existing business models running while exploring new, digitally driven ones, and decide how to split money and attention between the two. Alao found that middle managers, not just top executives, play a decisive role in resolving these conflicts.
Their approach shi fts depending on the stage of the process. When facing early uncertai nty, they hold contradictory ideas in mind at once rather than forcin g a premature choice. As plans firm up, they narrow the options down to a workable path forward. And when dealing with outside partners, t hey focus on justifying decisions in ways others will accept and trus t.
A close look at pet-care company PetCo showed this in action as it expanded into neighbouring markets. Resources shared with part ners - data, platforms, customer relationships - could either fuel gr owth for everyone or spark competition over the same pie. Handling th is well meant spreading leadership across the organisation rather tha n issuing orders from the top. Only when rivalry turned openly compet itive did senior leaders need to step in directly.
Two different playbooks for artificial intelligence
In his thesis Alao also examined how companies adopt AI, and found no singl e formula works. For predictable, well-understood applications, such as machine learning tools used to forecast outcomes, managers relied on established theory and proven methods, since performance expectati ons were clear and risks manageable.
For newer, less predictabl e applications, including generative AI, that approach fell short. He re, managers instead learned by building, testing and adjusting as th ey went, treating each step as an experiment rather than following a fixed plan.
Together, the findings paint digital transformation as less a technology problem than a people problem, one where the sh arpest strategic thinking often happens not in the boardroom, but sev eral rungs below it.
More information on the thesis
DESCRIPTION: Navigating Tensions in Digital Transformation: Managerial Action Across Levels Companies rushing into cloud computing, AI and other digital tools often assume the biggest hurdle is pickin g the right technology. New research by Ayomide Peter Alao suggests t he real challenge lies elsewhere: in the everyday judgement calls mad e by middle managers, caught between defending what already works and chasing what might work better.Established companies rarely have the luxury of starting from scratch, unlike digital-native riva ls. They must keep existing business models running while exploring n ew, digitally driven ones, and decide how to split money and attentio n between the two. Alao found that middle managers, not just top exec utives, play a decisive role in resolving these conflicts.Their appro ach shifts depending on the stage of the process. When facing early u ncertainty, they hold contradictory ideas in mind at once rather than forcing a premature choice. As plans firm up, they narrow the option s down to a workable path forward. And when dealing with outside part ners, they focus on justifying decisions in ways others will accept a nd trust.A close look at pet-care company PetCo showed this in action as it expanded into neighbouring markets. Resources shared with part ners - data, platforms, customer relationships - could either fuel gr owth for everyone or spark competition over the same pie. Handling th is well meant spreading leadership across the organisation rather tha n issuing orders from the top. Only when rivalry turned openly compet itive did senior leaders need to step in directly.Two differe nt playbooks for artificial intelligenceIn his thesis Alao a lso examined how companies adopt AI, and found no single formula work s. For predictable, well-understood applications, such as machine lea rning tools used to forecast outcomes, managers relied on established theory and proven methods, since performance expectations were clear and risks manageable.For newer, less predictable applications, inclu ding generative AI, that approach fell short. Here, managers instead learned by building, testing and adjusting as they went, treating eac h step as an experiment rather than following a fixed plan.Together, the findings paint digital transformation as less a technology proble m than a people problem, one where the sharpest strategic thinking of ten happens not in the boardroom, but several rungs below it.More inf ormation on the thesis END:VEVENT END:VCALENDAR