New episodes of the Sii Talks podcast: from AI strategy to real implementation challenges in organizations

Artificial intelligence is no longer just a trend – it is increasingly becoming an integral part of IT environments and everyday business operations. In the latest episodes of the Sii Talks podcast, experts share their experiences with implementing solutions based on Generative AI and Microsoft Copilot, highlighting not only the technology’s potential but also the real challenges organizations face after deployment.

AI as a new layer of IT infrastructure

In conversations with IT leaders from the automotive industry, a clear shift in the perception of AI emerges. Artificial intelligence is no longer treated as an add-on or an experiment. It is becoming another layer of IT infrastructure, positioned between data and business systems.

“AI is no longer a pilot project; it is becoming part of the IT architecture. This is a natural step for organizations that want to leverage data effectively” – emphasizes Sebastian Wiliński, EMEA&SA IT Director at Nexteer Automotive.

At the same time, experts point out that many organizations attempt to “skip” the preparation stage. In reality, it is the fundamentals such as data quality, well-organized processes, and a consistent approach to data governance, that determine whether AI becomes a real business enabler or simply another source of chaos.

The greatest benefits often come not from spectacular projects, but from areas where AI supports repetitive tasks such as report preparation, data analysis, or communication automation.

Enthusiasm and skepticism – two sides of the same technology

Although the potential of Generative AI is enormous, its accessibility also creates new risks, particularly among business users.

„Today, anyone can build an AI-based solution in just a few minutes. The problem begins when that speed is not accompanied by an understanding of the consequences, especially in terms of security and data quality” – notes Marcin Gajewski, CEO & President of the Management Board GMDigit Flow.

In practice, this means a growing risk of creating solutions that:

• work only “for demo purposes,”
• are not scalable,
• or use data in ways that are inconsistent with organizational policies.

On the other hand, companies that approach implementation strategically use AI to deliver highly practical improvements by reducing document preparation time, automating analyses, and supporting teams in their day-to-day work.

From implementation to adoption – the critical stage of transformation

The second episode focuses on an area that often determines the success or failure of an entire initiative: technology adoption.

“Today, the biggest challenge is not implementing the technology itself, but ensuring that employees actually use it. Without proper adoption, even the best tools fail to deliver business value” – says Marzena Oleszczuk, IT Digital Adoption Manager at Hitachi Energy.

Organizations that successfully implement tools such as Microsoft Copilot treat adoption as a separate process. It goes far beyond training and includes:

• building concrete use cases (e.g., report generation, meeting summaries, analyses),
• demonstrating quick wins,
• and supporting users in their everyday work.

More unconventional approaches, such as gamification, are also becoming increasingly popular. Instead of traditional training sessions, employees participate in challenges, test different AI use cases, and compete to find the most effective practical applications. This significantly accelerates adoption and builds genuine engagement.

People still at the center

A common conclusion runs through both conversations: artificial intelligence does not replace people, but it is rapidly transforming the way they work.

“AI is a tool that enhances human capabilities, but it does not replace responsibility for decision-making. People still remain at the center of the entire process” – adds Marzena Oleszczuk, IT Digital Adoption Manager at Hitachi Energy.

At the same time, differences in AI adoption are already becoming visible at the team level. Wherever technology is actively used, productivity is increasing noticeably faster.

AI in practice – what comes next?

The discussions clearly show that organizations are currently at very different stages of AI maturity, from early experimentation to consciously developed strategies.

“The key to success is not the technology itself, but the ability to embed it into processes and organizational culture. That is where real business value is created” – summarizes Sebastian Wiliński, EMEA&SA IT Director at Nexteer Automotive.

Regardless of the starting point, successful AI implementation depends on several critical factors:

• strong data foundations,
• well-designed processes,
• a conscious approach to security,
• and, increasingly important, effective user adoption.

Because today, AI is not transforming companies only at the strategic level. It is transforming them through everyday work.

Listen to the latest episodes of Sii Talks and discover what AI looks like in practice — from strategy to everyday business applications in organizations.

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