Beyond the hype – AI that delivers results event

From vision to action: AI that delivers real results and EBITDA impact

Munich, March 18th, 2025 | Artificial intelligence (AI) is no longer a futuristic concept – it’s a present-day force reshaping industries, revolutionizing workflows, and redefining competitive advantage. Beyond just operational efficiencies, AI has profound implications for a company's bottom line, influencing profit and loss (P&L) statements, optimizing resource allocation, and enhancing return on investment (ROI).

Yet, despite its transformative potential, many organizations find themselves stuck in the gap between ambition and execution. Unlocking these financial benefits requires a structured and pragmatic approach to AI adoption. At our Beyond the hype – AI that delivers results event, industry leaders shared actionable insights on overcoming these hurdles and turning AI into a competitive advantage.

Keep reading to dive into the event's key takeaways!

Organizations looking to integrate AI successfully should follow these five key recommendations:

1. Develop a clear AI vision and communication strategy

Leadership must articulate a clear AI strategy, setting expectations and aligning AI initiatives with business objectives. Transparent communication is critical to securing employee and stakeholder buy-in. However, a top-down mandate to become an "AI-first company" is not enough. Instead, starting small with a few curious AI users inside the organization can drive organic adoption among other colleagues who see the value of AI and follow the “early adopters”.

2. Establish AI expert task forces

Organizations should create dedicated AI teams with cross-functional expertise to oversee implementation, governance, and optimization. This ensures a structured and informed approach to AI adoption.

3. Invest in employee AI training

Upskilling employees is crucial for successful AI integration. Companies should provide AI training programs to bridge knowledge gaps and help employees adapt to AI-enhanced workflows. When it comes to new hires, a positive attitude towards AI is crucial and even more important than technical skills. Skills can and must be trained in a fast-evolving digital world, but an open-minded approach to tech, data, and AI is needed to do so.

4. Collaborate with external experts

Partnering with AI specialists, consultants, and technology providers can help businesses accelerate AI adoption, access cutting-edge innovations, and mitigate implementation risks. Last but not least, external experts can also address data issues.

5. Focus on solving specific business challenges

AI should be implemented with a problem-solving mindset rather than a technology-first approach. Organizations should identify specific pain points in their business and use AI to enhance productivity, efficiency, and decision-making.

The coming months will see rapid advancements in AI, reshaping industries and business operations. Key trends to watch include:

AI-generated code

AI models are expected to automate software development at an unprecedented scale. Dario Amodei, CEO & Co-Founder at Anthropic, even claims that in the next 3-6 months AI will be writing 90% of the code, and in 12 months, nearly all code may be generated by AI. This also removes the “middleman” from the development process: With the appropriate AI tools, ideas for applications can be implemented immediately, often without the need to brief a programmer.

Vertical SaaS applications

Industry-specific AI-powered software solutions are expected to see rapid growth as businesses look for highly specialized tools tailored to their needs. These applications will allow companies to leverage AI in ways that address industry-specific challenges, such as supply chain optimization in manufacturing, predictive analytics in healthcare, and fraud detection in financial services. The increasing availability of AI-powered SaaS solutions will make it easier for organizations to deploy AI without the need for extensive in-house development.

AI-to-AI communication

AI systems will increasingly interact with each other, creating more autonomous and intelligent ecosystems. This development will improve automation, streamline operations, and reduce human intervention in data exchange and decision-making. From chatbots collaborating to provide seamless customer support to machine learning models working together for predictive maintenance in industrial settings, AI-to-AI communication will redefine efficiency and scalability across industries.

Decreasing AI costs

As AI technology advances, the cost of large language models and computing power is expected to decline significantly. This will make AI adoption more accessible to businesses of all sizes, enabling even small and mid-sized enterprises to implement AI-driven solutions. Lower costs will also encourage further experimentation and innovation, allowing companies to test AI applications with minimal financial risk before scaling up.

Integration of AI systems

Rather than using AI in isolated applications, businesses will focus on integrating multiple AI solutions into cohesive, intelligent ecosystems. This integration will ensure smoother workflows, better data utilization, and more comprehensive automation across different business functions. Companies will prioritize interoperability between AI tools, ensuring that data flows seamlessly between systems to enhance decision-making, streamline operations, and improve customer experiences.

We spend a lot of time on boards with management teams, and the knowledge gap in the area of AI and data has never been bigger than it is today. Many CEOs still think AI is a tech problem for the CIO to handle.

Dr. Stefan Sambol Founding Partner at OMMAX

Discover the full event insights, including how to overcome challenges and a deep dive into AI as a productivity powerhouse, and how to make AI your competitive advantage by following the link below:

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