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.
Technology moves faster than the institutions trying to explain it. Public bodies, regulators, and corporates end up with digital channels that look active but say very little, while the audiences they need to reach lose patience. The gap between what an organisation does on emerging tech and what it manages to communicate has become its own strategic risk.
Most growth plans assume the same playbook that built the business will scale it. It rarely does. Leaders inherit revenue targets that demand a different sales motion, a sharper customer thesis, and a willingness to rebuild commercial functions while the quarter is already running.
Retail leadership teams are running two organisations at once: a legacy operation built around store footprint, seasonal buying and broadcast marketing, and an emerging one shaped by AI personalisation, gamified loyalty and immersive commerce. The capital is flowing into the second, the revenue still sits in the first, and most boards cannot tell which experiments are worth scaling and which are theatre. The question is not whether AI changes retail. It is which bets pay back inside the planning cycle.
Most strategy processes treat the future as uncertain and respond by hedging. That posture costs time and investment while competitors move on signals that were knowable in advance. Leadership teams need a disciplined way to separate the parts of the future that are already decided from the parts that are still open, and to act on each differently.
Established companies are being disrupted by platform businesses built on assets those companies already own. Legacy structures, customer relationships, and proprietary data are competitive advantages, but only if the organisation knows how to activate them as platforms. Most do not.
Most large organisations have run AI pilots. Very few have turned them into an operating model that moves revenue, cost or risk at the scale of the business. The gap is not the technology. It is leadership conviction, governance design and the discipline to industrialise what works before the next cycle of tools arrives.
Building a category-defining consumer platform without venture capital forces every commercial decision into sharper relief. Founders who scale that way have to make pricing, content, partnerships and community choices that compound for two decades, not two funding rounds. The discipline that produces is rare, and difficult to teach from a textbook.
Most organisations invest in technology to do the same work faster. That gap – between efficiency and genuine effectiveness – is where digital transformation programmes stall and where competitive advantage quietly disappears. As generative AI accelerates the pressure to adopt, leaders face the same trap at greater speed: automate the existing, rather than reinvent what is possible.
Buyers now research, compare, and decide long before a sales team hears their name. The old machinery of press releases, campaign calendars, and interruption advertising was built for a slower world and is increasingly invisible to the people it is meant to reach. The gap between how companies market and how customers actually buy is where growth is being lost.
Boards setting Asia strategy are working with thin signal. Reporting from the region is fragmenting along national, linguistic, and political lines, and the gap between official narratives and on-the-ground reality is widening. Leaders need an interlocutor who can sit between Western boardrooms and Asian political reality without flattening either.
Most leadership teams now have an AI strategy on paper and very little operating conviction behind it. The question senior executives are actually asking is narrower and harder: which emerging technologies will compound into advantage, which will absorb capital and produce nothing, and how do you tell the difference early. Few people have lived both sides of that question, building a category from scratch and then placing hundreds of bets on what comes next.
Most organisations have committed to an AI strategy. Very few have built the governance architecture to make that strategy accountable at scale. The gap between an approved AI roadmap and actual enterprise-wide adoption is where initiatives stall, risk accumulates, and boards are left approving decisions they cannot yet evaluate. Closing that gap requires a different kind of expertise – one built inside organisations, not just around them.