{"id":112055,"date":"2025-12-16T15:53:35","date_gmt":"2025-12-16T14:53:35","guid":{"rendered":"https:\/\/simplifier.io\/?p=112055"},"modified":"2025-12-16T16:53:48","modified_gmt":"2025-12-16T15:53:48","slug":"register-now-for-the-it-online-conference-in-january-2026","status":"publish","type":"post","link":"https:\/\/simplifier.io\/en\/ai\/register-now-for-the-it-online-conference-in-january-2026\/","title":{"rendered":"AI: What companies really need – and what they don’t."},"content":{"rendered":"
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Okay, what’s up?<\/h4>\n

Artificial intelligence is currently everywhere. In keynotes. In pitch decks. In LinkedIn posts with rocket emojis \ud83d\ude80.
\nAnd sometimes even in places where nobody has seriously ordered them. The feeling is: <\/p>\n

If you don’t have AI today, you will be irrelevant tomorrow.<\/strong><\/p>\n

However, the reality in many companies is different. There are overstretched IT teams, unclear responsibilities, security concerns, a whole collection of different AI tools, a progressive boss, a mood somewhere between euphoria and rejection, enthusiastic consultants – and the quiet question in the background: “Is this really helping us right now – or are we just building the next technological construction site?” … Welcome to the AI madness. <\/p>\n

Between AI chaos and pilotitis<\/strong><\/h4>\n

In the last two or three years, AI has shot from a niche topic to the top of every board agenda – but that doesn’t mean that companies really know how<\/em> to use AI effectively. A look at the reality of AI deployment in 2025<\/strong> shows a very mixed picture: a lot of movement, a lot of hype – and yet surprisingly little clear strategy. Current data shows that the majority of companies are using AI at least somewhere today<\/strong>: Around 78% of companies<\/strong> worldwide use AI in at least one business function<\/strong> – such as marketing, customer service or data analysis.(The Global Statistics<\/a>). However, this does not mean that AI is strategically anchored. Many of these applications are selective tools<\/strong> – not embedded in well thought-out business processes. <\/p>\n

AI tools in everyday life, but without governance<\/strong><\/p>\n

Generative AI assistants such as ChatGPT, Copilot, DeepL & Co. have changed digital work: Almost half of companies already use such tools for writing and translation tasks, research or simple automation.(PwC<\/a>). But beware: in many cases, this is done without official approval, without a security check and without a data strategy<\/g> – for example, when employees use AI tools “on the side” and enter sensitive information into external models. A recent survey shows that 93% of employees in US companies use AI tools that have not actually been officially approved<\/strong>.(CRN<\/a>). This is not just a hype problem – but a governance and security problem of the first order.<\/strong> <\/p>\n

The data from company surveys show two sides of the coin: on the one hand, AI has arrived in everyday life: Recruitment, onboarding, training, communication – people are at least experimenting everywhere.(manpowergroup.de<\/a>). On the other hand, many companies lack a company-wide AI strategy<\/g>: most AI implementations remain isolated projects rather than part of a long-term, scalable transformation program. Only<\/strong> around a third of companies even have a clear idea of how AI should be integrated on a broad basis<\/strong> – the rest are often still in “pilotitis”.(henleyresearch.com<\/a>). <\/p>\n

Skills and culture problem: AI cannot replace someone who does not know how to manage it<\/strong><\/p>\n

People are a central hub in the field of AI experimentation. Studies show that although a large proportion of the workforce uses AI tools, they do not feel sufficiently prepared for them<\/strong>: in a global survey, only around 36% said they were well enough prepared to use AI effectively on the job<\/strong>.(BCG Global<\/a>). This leads to two typical patterns in companies: Wild growth in tool use<\/strong> (employees use AI “just like that” – but without common rules, without data and security specifications) andstrategic blockades<\/strong> (at management level, there is either no plan for how<\/em> AI should contribute to value creation, or the tools remain stuck in proof-of-concepts because no one is “leading them into the organization”). <\/p>\n

Industry and size differences: Large companies vs. medium-sized companies<\/strong><\/p>\n

There is a clear effect of company size: large corporations integrate AI in several areas at the same time – from customer service to supply chain to product development.(The Global Statistics<\/a>). Although small and medium-sized companies are following the trend, they are often only at the entry level: selective use cases, less deep integration, more experimental use without governance. <\/p>\n

AI practice is not a sprint, but a marathon<\/strong><\/h4>\n

AI adoption in 2025 is clearly on the rise – almost every company is using some form of AI tool today. But: <\/p>\n