AI at Work from Productivity Hacks to Organizational Transformation 2026

On augmentation, companies consistently describe AI less as a discrete tool to perform routinized tasks and more as a general-purpose collaborator. Specifically, the rise of agentic AI allows AI to take independent action, enabling the emergence of “digital workers” that work side by side with humans. The promise is a future where human workers are being augmented with a fleet of agents that extend their reach and capabilities. Such usage of AI positions workers as orchestrators supervising AI systems that generate the options, analyse big data and simulate scenarios.In this view, the promise of AI lies not only in efficiency gains but also in navigating new distributions of labour that emphasize human judgement being reserved for oversight, final decision-making and organizational learning. Notable examples can be found in client-facing positions, where professionals want to dedicate most of their efforts to problem-solving and developing customized solutions in collaboration with clients (see Box 2). Automating beyond expectations BOX 1 When AI first entered the workplace, many assumed its reach would be confined to repetitive or clerical tasks. C&T companies now report that it is extending much further, into domains once considered judgement-heavy: –Drafting and redlining contracts – AI agents now handle contract preparation and risk flagging in legal functions that once required junior lawyers. –Multiway invoice matching in finance – AI systems perform complex cross-checks in financial operations, a task previously reserved for experienced analysts. –Design iteration – AI enables account executives and solution consultants to co- create higher-fidelity prototypes with clients, which reduces mundane tasks and accelerates the design process. The promise, companies argue, is not to eliminate professional roles but to relieve them of their most time-consuming and less-interesting repetitive burdens, allowing humans to focus on negotiation, oversight and client engagement.Importantly and surprisingly, companies report that AI already excels at performing complex tasks – not just rote or clerical work, but judgement-heavy domains such as contract review, compliance checks and design iteration (see Box 1). These observations suggest that the boundaries between automatable tasks and judgement-intensive, professional work are thinner than was once assumed. In practice: Celonis is working with one of Europe’s largest manufacturers of premium packaging steel to achieve real-time visibility of its material flows and, as a result, allow it to better anticipate supply-chain risks and ensure planning stability. Using AI, the company is minimizing scrap from unsold materials and automatically identifying the best customer for potential scrap materials, with human-in-the-loop validation for adjustments. The AI-powered tool then generates structured email offers, letting customers review, approve, reject or modify an order for these materials with just one click.