Digitale Transformation
Strategen und Technologen unterstützen Organisationen bei den technischen, kulturellen und kommerziellen Anforderungen der digitalen Transformation
Speakers Associates represents 234 speakers on Digitale Transformation, including Rahaf Harfoush, Purna Virji, Itai Green, Limor Ziv, Tom Goodwin, Daniel Trabucchi & Tommaso Buganza, Jeremy Blain, Dr Sidney Shapiro, Blake Morgan und Marc Saltzman.
Most large organisations have run AI pilots. Very few have moved them into operating reality. The gap is rarely about the technology. It is about governance, internal capability, legacy stacks and the absence of senior leaders who can credibly translate AI from a vendor pitch into a portfolio of operational bets.
Blockchain and digital currency have moved from curiosity to board-level question, and most executives still cannot separate the credible use cases from the noise. Regulators are writing rules in real time, and early decisions about custody, tokenisation, and settlement will shape cost structures for a decade. Leaders need a translator who has sat on both sides of the table, inside government and inside the research lab.
Most incumbents still treat digital as a function, not a structural reset of how the business competes. Boards then find themselves asking a chair or CEO to run two operating models at once, one built for the company they inherited, one built for the company the market now demands. Governance, leadership style, and commercial instinct all have to move at the same time, and few leaders have done it at scale.
Most large organisations are reacting to AI and digital disruption, not directing it. Leadership teams know the operating model needs to change but keep funding incremental programmes that preserve the status quo. The harder question is how to spot the shifts that matter, get the company aligned around them, and turn innovation from theatre into a measurable change in how the business runs.
Global supply networks were built for a world of open trade, cheap logistics, and predictable demand. None of those conditions hold any longer. Boards now face a live question: how do you keep cost discipline, meet customer commitments, and re-engineer operations for a fragmented tariff environment, all at the same time, and without stalling growth?
Most executives have mapped their AI technology landscape; far fewer have mapped the governance architecture being built around it. The EU AI Act now sets binding constraints on which AI applications can be deployed, which require conformity assessments, and which are prohibited entirely. Parallel frameworks at UN level will extend these obligations globally.
Most retail and consumer businesses can list the trends shaping their category. Few can turn that awareness into operational change before competitors do. The gap is not insight, it is the discipline to test, adapt, and scale what works while leaving the theatre of innovation behind.
Most organisations have AI budgets. Most are still running pilots. The problem is not investment – it is that AI has been framed as a strategy in its own right, which turns a deployment decision into an open-ended design problem. Meanwhile, the gap between AI experimentation and scaled competitive advantage is narrowing fast. Organisations that cannot move AI into production – aligned to business goals they already have – will cede ground to those that already have.
For two decades, the economics of distribution favoured the hit. Digital shelves, open-source tooling and cheap production have quietly inverted that logic, and most organisations still plan their assortment, pricing and manufacturing as if scarcity were the default. The unresolved question for commercial leaders is how to build a growth strategy when niche demand, zero-cost copies and distributed production are each reshaping the economics at the same time.
Digital channels keep multiplying. Customer attention keeps shrinking. Marketing budgets rise while response rates fall, and pushing harder now produces more noise without more trust. The commercial question has shifted from how to reach more people to how to keep the ones who already know you.
Incumbent banks are facing increasing competition from challenger institutions that now match them on product and user experience. The more complex question is how banking will evolve as money and data become increasingly programmable, and who will control the underlying infrastructure.
Most large organisations now claim an AI strategy and an innovation function. Few can show what either has produced in the last twelve months. Pilots multiply, capability stalls, and the question of how to move from experimentation to operating advantage stays open.