Digital Business & Future 08.06.2026

11 min read

88 percent of companies worldwide are now using AI in at least one business function. In Germany, adoption has doubled in a single year-from 20 to 41 percent. Yet only a small minority are seeing measurable business value. By 2026, the divide will separate those who turn AI from an experiment into core infrastructure from those who fall behind.

Key Takeaways

The adoption gap is closing, but the value creation gap remains

The numbers paint a paradoxical picture. On one hand, according to McKinsey’s “State of AI” study from November 2025, 88 percent of companies worldwide now use AI in at least one business function. That’s a ten-percentage-point increase over the previous year. The study is based on a survey of 1,993 participants from 105 countries.

In Germany, Bitkom’s spring 2026 study reveals an even more dramatic shift: 41 percent of companies with 20 or more employees are actively using AI. A year earlier, the figure was 17 percent. Another 48 percent are planning or discussing implementation. Only 11 percent now say AI is not on their radar-down from 20 percent at the end of 2024, according to the Federal Statistical Office.

On the other hand, only 39 percent of global companies report measurable EBIT impact from AI. Most of those see less than a five-percent improvement in results. Just six percent qualify as “high performers” that systematically extract value from AI, McKinsey finds. Nearly two-thirds have yet to begin scaling AI across the enterprise.

Sources: Bitkom, 2026 / McKinsey State of AI, November 2025

BCG’s study of 1,250 executives across nine industries reaches a similar conclusion: the five percent of companies BCG labels “future-built firms” achieve twice the revenue growth and 40 percent higher cost savings in the areas where they deploy AI. These leaders plan to invest more than twice as much in AI as their peers. The gap is widening, not shrinking.

For mid-sized companies, the message is clear: simply introducing AI tools is no longer enough. In 2026, the focus must shift to embedding AI into processes, decision-making structures, and business models. Treating AI as an isolated IT project risks falling behind competitors who already see it as a core strategic pillar.

AI agents become the new operational standard

The biggest technological leap in 2026 will be AI agents: autonomous systems that independently plan, execute, and learn from results. Unlike chatbots that respond to individual queries, AI agents actively pursue predefined goals across multiple steps. They leverage external tools, make intermediate decisions, and adapt their strategy when conditions change.

According to McKinsey, 62 percent of surveyed companies are already experimenting with AI agents. 23 percent are already scaling at least one agent-based system in parts of their business. Major platform providers are driving this trend: Salesforce has closed over 18,000 deals with Agentforce since October 2024, while Microsoft Copilot Studio is used by more than 230,000 organizations worldwide.

SAP reports that 67 percent of all cloud orders in Q4 2025 included business-AI components. Joule, SAP’s AI assistant, is now integrated into more than 80 percent of the most-used tasks and boasts over 2,400 prebuilt skills. The ninefold increase in Joule adoption in 2025 underscores how quickly AI agents have moved from niche to mainstream.

BCG estimates that AI agents already account for 17 percent of total operational and analytical AI value. By 2028, that share is expected to rise to 29 percent. For SMEs, this means: anyone modernizing ERP, CRM, or HR systems today must factor in agent capabilities from day one. Retrofitting later will cost more than planning ahead.

Satya Nadella stressed at the 2026 World Economic Forum in Davos that the focus now must be on separating “spectacle from substance.” AI must deliver measurable outcomes, not just impressive demos. Satya Nadella, Microsoft CEO, Davos 2026 (paraphrased)

2.52 trillion dollars: the investment race gathers pace

Global AI spending is forecast to reach 2.52 trillion US dollars in 2026, according to Gartner-up from 1.5 trillion in 2025. Generative-AI outlays alone are growing 80.8 percent. Data-center costs will top 650 billion dollars in 2026, a 31.7-percent jump year over year.

IDC projects worldwide corporate AI investments will hit 632 billion dollars annually by 2028, up from 307 billion in 2025. The bulk is no longer flowing into pilot projects but into production systems: ERP integration, process automation, and data-driven decision support.

For SMEs, two realities emerge. First, AI features in standard software from SAP, Salesforce, and Microsoft 365 are becoming the norm; companies need to master the AI functions already embedded in their tools rather than build bespoke models. Second, the opportunity cost of staying on the sidelines is rising: rivals that automate quoting, fine-tune supply chains, and auto-respond to customers will make inaction the most expensive choice of all.

EU AI Act: Regulation Takes Concrete Shape

On 2 August 2026, the requirements for high-risk AI systems under Annex III of the EU AI Act come into force. Affected areas include AI in personnel decisions, credit lending, education and law enforcement. Companies must establish risk management systems, maintain technical documentation, meet transparency obligations and ensure human oversight.

A Bitkom study reveals that 77 percent of German companies using AI see an improved competitive position. At the same time, 53 percent cite legal uncertainties and the EU AI Act as their biggest hurdles. A lack of technical know-how (53 percent) and staff shortages (51 percent) also pose challenges. The three largest obstacles are therefore not technical but organizational in nature.

Compliance consultants estimate initial adaptation costs for mid-sized companies at between €500,000 and two million euros, plus ongoing annual costs of a similar magnitude. The actual burden depends on how many high-risk systems a company operates and how far its existing documentation already extends.

This is no cause for panic, but it is a call to action. Companies introducing new AI systems or modernizing existing ones should factor in compliance requirements from the outset. Retrofitting in August 2026 will be far more expensive than building them in during implementation.

Case Study: How TRUMPF Brings AI into Production

Machine-builder TRUMPF from Ditzingen illustrates how mid-sized manufacturers can integrate AI in practice. In February 2025 the company launched an internal AI hub and in April 2025 released the “Cutting Assistant.” The system analyzes laser-cut edges via smartphone scanner and, after roughly five iteration loops, suggests optimized cutting parameters-no programming skills required.

In parallel, TRUMPF is rolling out remote monitoring expected to deliver a 20 percent efficiency gain in machine operation. The strategy follows a clear pattern: no headline-grabbing moonshots, but incremental integration into existing production processes with measurable benefits. The AI hub consolidates various initiatives and ensures that lessons learned in one area are systematically transferred to others.

Cross-industry data confirms this approach. According to a Maximal-Digital study, about one-third of German mid-sized firms already use AI, while nearly one-quarter are piloting it. Seventy-three percent leverage generative AI, 12 percent predictive AI and 10 percent are testing early AI agents. The breadth shows there is no single AI use case. The entry point is wherever the pain point is most acute.

Skills: The Overlooked Bottleneck

The World Economic Forum’s Future of Jobs Report 2025 predicts 170 million new roles and 92 million roles lost globally by 2030, a net gain of 78 million jobs. Yet 59 of every 100 workers will need reskilling or upskilling. Seventy-seven percent of employers already plan corresponding programs. Qualification requirements in AI-exposed occupations are changing 66 percent faster than in less-affected roles.

PwC adds the economic perspective: in sectors with high AI penetration, productivity growth between 2018 and 2024 was nearly four times higher than in 2018–2022-27 percent versus 7 percent. Employees with AI skills earn 56 percent more worldwide than comparable colleagues without them. This premium has more than doubled in a single year, from 25 to 56 percent. The analysis draws on nearly one billion job postings across 24 countries.

For mid-sized companies this means AI competence is not a nice-to-have for the IT department but a strategic competitive lever. To attract and retain talent, executive teams must make AI upskilling a leadership priority-extending beyond developers and data scientists to every role that makes data-driven decisions: procurement, sales, controlling, HR.

Conclusion: Three Priorities for 2026

The next phase of AI is no longer a technological question, but a business one. The data is clear: adoption alone is not enough. Differentiation lies in systematic integration. Three priorities for mid-market leaders:

First: Embed AI agents into existing systems. SAP Joule, Salesforce Agentforce, and Microsoft Copilot provide the infrastructure. The leverage comes from configuration and process redesign-not from building proprietary models. 67 percent of SAP Cloud orders already include business AI. Ignoring this means paying for features you never use.

Second: Build the EU AI Act into ongoing projects now. August 2026 is just five months away. Deploying high-risk AI requires risk management systems, documentation, and oversight structures. The cost of retrofitting far exceeds that of early integration.

Third: Treat upskilling as a leadership responsibility. By 2030, 59 percent of the workforce will need new skills. Employees with AI competencies earn 56 percent more. Failing to drive this change erodes both productivity and talent retention.

Frequently Asked Questions

What is the AI adoption rate among German companies in 2026?

41 percent of companies with 20 or more employees are actively using AI. Another 48 percent are planning or discussing implementation. Only 11 percent say AI is not on their agenda. These findings come from the Bitkom study 2026, based on a survey of 604 companies conducted during calendar weeks 2 to 6 of 2026.

What are AI agents and why are they relevant for businesses?

AI agents are autonomous systems that independently plan, execute, and learn from tasks. They actively pursue predefined goals across multiple steps. Platforms like SAP Joule, Salesforce Agentforce, and Microsoft Copilot integrate these capabilities into standard business software. According to McKinsey, 62 percent of companies are already experimenting with them.

When do the high-risk obligations of the EU AI Act come into force?

On 2 August 2026, the requirements for high-risk AI systems under Annex III take effect. This affects AI in personnel decisions, credit lending, education, and law enforcement. Companies must demonstrate risk management systems, technical documentation, transparency obligations, and human oversight.

What does compliance with the EU AI Act cost SMEs?

Compliance consultants estimate initial costs at 500,000 to 2 million US dollars, plus ongoing annual costs of a similar magnitude. Actual costs depend on the number of high-risk systems and the state of existing documentation.

How can SMEs leverage AI without developing their own models?

The biggest levers lie in using AI features within existing software. SAP, Salesforce, and Microsoft are embedding AI agents directly into their platforms. Configuration and prompt engineering can deliver concrete added value. TRUMPF’s “Cutting Assistant” shows how production-adjacent AI can be used without programming skills.

Which industries benefit most from AI?

According to PwC’s AI Jobs Barometer 2025, productivity growth in AI-intensive sectors is nearly four times higher than the average. Financial services, manufacturing, logistics, and healthcare see the strongest gains. Employees with AI skills command a 56 percent salary premium.

How much is the world investing in AI?

Gartner projects global AI spending will reach 2,520 billion US dollars in 2026, up from 1,500 billion the previous year. Spending on generative AI alone is growing by 80.8 percent. IDC forecasts 632 billion dollars annually for AI solutions by 2028, starting from 307 billion in 2025.

Source for header image: Pexels / Pavel Danilyuk

Image source: Pexels / Pavel Danilyuk

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