Trasformazione digitale
Strateghi e tecnologi che aiutano le organizzazioni ad affrontare le sfide tecniche, culturali e commerciali della trasformazione digitale
Speakers Associates represents 234 speakers on Trasformazione digitale, including Rahaf Harfoush, Purna Virji, Itai Green, Limor Ziv, Tom Goodwin, Daniel Trabucchi & Tommaso Buganza, Jeremy Blain, Dr Sidney Shapiro, Blake Morgan, e Marc Saltzman.
Markets are not behaving like markets anymore. Categories collapse, customer expectations shift mid-quarter, and the playbook that built the business is now the thing slowing it down. Senior teams know the brand needs to change shape; the harder question is which parts to keep and which to break on purpose.
Most organisations can produce content. Very few can build an audience that comes back daily. The gap between publishing and habit is where budgets quietly disappear, and it is rarely closed by adding channels or hiring more creators. It is closed by people who know how to design a format, pick the right voices, and run the commercial side of attention.
Most boards now own an AI strategy on paper. Very few can describe the governance, the deployment route, or the human-machine boundary their organisation will actually operate against once the pilots end. The harder question is not whether to invest, but how to make defensible decisions about autonomy, accountability, and workforce design when the technology is moving faster than the policy around it.
Most enterprises have bought into generative AI in principle and stalled in practice. Pilots multiply, demos impress, but very few make the jump to operating on proprietary data inside real workflows. The hard question for boards is no longer whether to adopt AI, but how to make it useful at scale without losing control of accessibility, governance and the workforce alongside it.
Generative AI has moved faster than most operating models can absorb. Boards approve pilots, then stall on how to make the technology work inside real processes, real teams and real customer experiences. The gap between technology curiosity and operating capability is where transformation programmes lose momentum.
Most organisations have run AI pilots. Few have moved beyond them. The gap is not technological – it is organisational. Building the internal structures, teams, and decision-making capacity to deploy AI at scale is the challenge most leadership teams have not yet solved. Without a systematic approach, AI investments accumulate without compounding.
Most boards are now expected to take a public position on AI and immersive technology before the rules that will govern them exist. They are making capital decisions on cities, infrastructure and customer environments under standards that are still being drafted. Knowing who is writing those standards, and how to align to them early, has become a leadership question, not a technical one.
Most mid-sized European companies have run AI pilots. Few have moved them into operating reality. Boards are stuck between vendor pitches, internal scepticism, and a workforce already split between people who use AI daily and people who don’t.
Most boards have approved an AI strategy. Far fewer can explain how their models make decisions, where the bias sits, or what they will say to a regulator when one of those decisions is challenged. The gap between procurement and accountability is widening, and the answer is not another tooling vendor.
Most large companies have an innovation problem they cannot solve internally. They have signed memoranda with startups, run accelerators, opened innovation labs, and still struggle to convert any of it into operating advantage. The gap is not strategic intent. It is the practical discipline of partnering across a size and culture asymmetry that defeats most corporate teams.
Most organisations have already run AI pilots. The harder question is what happens after the proof of concept ends. Procurement standards stay unclear, accountability for AI-assisted decisions is unassigned, and the governance frameworks people quote in slides do not survive contact with real workflows. Leadership teams cannot say with confidence which decisions AI should be trusted with and which it should not.