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 senior teams have run their first generative AI pilots and stalled. The technology is general-purpose, but the operating decisions are not: which workflows to redesign, which tools to standardise on, where hallucination is tolerable and where it is not. The question is no longer whether to adopt, but how to convert curiosity into measurable operating advantage without ceding judgement to the model.
Most digital transformation programmes deliver less than the business case promised. The reason is rarely the technology. Teams cannot make defensible decisions at speed because trust, candour, and psychological safety have been allowed to erode quietly while tech debt got the spreadsheet.
Financial firms are under pressure to put generative and agentic AI into regulated work without breaching rules, losing trust, or building tools advisers ignore. Most boards can describe the opportunity; far fewer can describe the operating model, the controls, or where an agent stops helping and becomes a liability. The gap between AI ambition and deployment that creates value without eroding the business model is where most programmes stall.
Most boards are now asked to approve AI decisions they do not understand, under regulation that is still settling. The hard work is no longer pilots. It is deciding where AI belongs in the operating model, who is accountable when it fails, and how to defend those choices to regulators, customers and employees.
Most large companies still treat innovation as a creative event rather than a managed discipline. The teams shipping new products lack the metrics, governance, and decision rules that the core business takes for granted, so good ideas stall and bad ones consume capital for too long. Growth then depends on individual heroics instead of a repeatable system.
Technology is getting more capable faster than the people using it are getting more skilled. Most digital products are designed for efficiency, not for the human nervous system, and the gap shows up in fatigue, disengagement and shallow adoption. The question for leaders is no longer how to deploy AI faster, but how to design it so people actually want to live with it.
The middle ground that organisations were built around is thinning out, and the rate at which it thins is itself accelerating. Intermediaries lose their role, the nation state loses its monopoly on power, and customers and employees move to the edges. Senior teams have to decide which structures still pay back, which have quietly stopped working, and how to plan when the cycle of change is shortening.
Most leadership teams have too many strategic priorities and no reliable basis for choosing between them. The result is organisations that are active but not competitive – sustaining wide portfolios of initiatives while their value proposition to customers and talent quietly weakens. Deciding what to stop doing is the harder strategic question, and most frameworks leave executives without a method.
Most technology leaders are asked to deliver speed, resilience and measurable performance with a flat budget and a shrinking error tolerance. The leadership conversation has moved past digital transformation as a project and now sits inside the operating model itself. What executives want is a working picture of how IT, data and AI compound into competitive advantage when decisions are made in seconds and failure is public.
Most leaders now agree that AI will reshape their workforce. Fewer can say what that looks like on a Monday morning for a marketing coordinator, a finance analyst or a field engineer. The distance between boardroom AI strategy and the person being asked to use the tools is where adoption stalls, budgets leak and cultural resistance hardens.
Organisations are deploying AI capabilities faster than they are building the governance structures to manage them. The gap between what technology can do and what leadership has decided it should do keeps growing. The harder question is not whether to automate but what must remain human – and most boards do not yet have a framework to answer it.
Most retail and consumer businesses now operate across physical, digital and virtual channels at once, but their org charts, P&Ls and brand playbooks still assume a single dominant channel. The result is fragmented customer experience, duplicated investment, and a leadership team unsure which version of the business it is actually running. The harder question is what to centralise, what to redesign, and what to stop doing entirely.