The Survey: AI Adoption in Practice

A study by the technology and management consultancy Campana & Schott, which surveyed more than 200 executives responsible for AI and digitalisation across Germany, Austria and Switzerland, contradicts the prevailing narrative that artificial intelligence is mired in crisis. Instead, roughly four out of five respondents reported concrete improvements in efficiency and productivity through generative AI. Moreover, the technology has moved well beyond the pilot stage: AI agents are already operating in IT support, customer service, and even project management.

The survey, now in its eighth iteration as part of the German Social Collaboration Study, found that nearly 85 percent of executives would not want to go without generative AI in their daily work. At the same time, organisational structures are beginning to mature – around a quarter of companies have already established formal initiatives such as “Centres of Excellence” or “Agent Factories” to standardise AI deployment.

Despite this enthusiasm, leaders do not ignore the risks. Security and compliance topped the list of concerns, yet the survey data and commentary suggest these are manageable. Participants pointed to the availability of enterprise-grade AI solutions that keep corporate data out of model training, meet GDPR requirements, and can even be operated on-premises for highly regulated sectors like banking, insurance and healthcare.

The most striking finding, however, lies elsewhere: 83 percent of those surveyed see an urgent need to build AI competence and expand training – a task that the executives themselves admitted they have not yet adequately addressed.

Why the Public Debate Misses the Boardroom Reality

Security and Compliance: Not the Showstopper Some Claim

The survey reveals that while data protection and compliance worries persist, they are being tackled systematically. Organisations have established clear governance structures, access controls, and anonymisation procedures. Enterprise AI offerings now routinely separate customer data from model training, complying with the EU’s GDPR. For regulated industries, hosting language models in a private cloud or on dedicated servers provides an extra layer of control. These measures transform security from a potential crisis into a manageable configuration task.

The Training Deficit: A Self-Inflicted Roadblock

The fact that 83 percent of executives identify workforce upskilling as their biggest gap – and simultaneously acknowledge that it is their own responsibility – is a candid admission. The technology is already deeply embedded in daily operations, yet systematic skill-building lags. The survey report likens this to “an unfinished homework assignment.” Without a structured approach that goes beyond ad-hoc IT-department workshops, companies risk having powerful tools that their employees cannot use effectively.

Competitive Imperative

The message from the study is clear: the firms that are moving fastest are no longer debating whether to adopt AI but are focused on how to use it responsibly and at scale. Those still stuck in the public “crisis” narrative are losing valuable time. The survey’s author, Campana & Schott associate partner Sven Hausen, warned that while some discuss pros and cons, others are already accumulating experience and building durable competitive advantages.

Closing the AI Competence Gap

Based on the survey insights, DACH business leaders should take immediate steps to turn the training gap into a strategic advantage:

  • Launch a company-wide AI upskilling programme. With 83 percent of peers admitting the need, moving beyond sporadic training to a systematic curriculum is essential. Start by identifying which roles – not just IT – will most benefit from generative AI literacy.
  • Adopt enterprise AI platforms with built-in compliance. The survey shows that security fears can be calmed by using tools that guarantee data isolation and GDPR conformity. This removes a psychological barrier to broader deployment.
  • Formalise AI governance now. Nearly a quarter of surveyed firms already run Centres of Excellence. If your organisation hasn’t, establish clear responsibilities, usage guidelines, and a cross-functional steering committee to scale best practices.
  • Deploy AI agents in proven areas first. The study highlights IT support, customer service and project management as early wins. Use these successes to demonstrate tangible productivity gains and build internal momentum.

Risk & Opportunity Assessment

Commercial RiskMediumWhile AI can raise productivity, delaying the systematic training and governance highlighted by the survey could erode the efficiency gains that four-fifths of peers are already capturing, turning the gap into a sustained commercial handicap.
Competitive RiskHighThe report explicitly warns that companies still debating AI’s merits risk falling behind those that are already accumulating hands-on experience and building durable competitive advantages through day-to-day use.
Regulatory RiskLowSurvey participants confirm that GDPR-compliant enterprise AI solutions, on-premises deployment for regulated sectors, and established governance frameworks have turned data protection into a manageable operational task rather than a showstopper.
Reputation RiskLowThe survey shows no reputational penalty from AI adoption; on the contrary, early movers are seen as progressive, and the public crisis narrative does not reflect internal corporate perception.
Technology DisruptionMediumGenerative AI continues to evolve rapidly, and companies that ignore it risk being disrupted by more agile competitors. However, the immediate technology risk is one of falling behind in adoption rather than an imminent existential threat.
Commercial OpportunityHighFour-fifths of responding executives report concrete efficiency and productivity gains; embedding AI with proper governance and workforce training can convert that into a lasting margin and competitive advantage.