In September, Ommax together with Amazon Web Services (AWS), brought together tech, digital, and AI experts, industry pioneers, and leading investors to discuss how businesses can turn AI theory into tangible outcomes.
While AI’s potential is widely acknowledged, only 12% of German SMEs are deploying AI solutions (BMWK). What’s holding them back?
In the panel discussion on “Transforming Businesses with Data & AI” Dirk Eisenberg (stp.one), Dominik Mühl (Marondo Capital), Salini Nair Avanupurath (AWS), Matthias Patzak (AWS), Evan Canfield (AWS), Christian Brugger (OMMAX), and Toni Stork (OMMAX) shared their insights.
Artificial Intelligence (AI) is transforming industries, but in Europe, only a small number of companies are actively deploying AI solutions. The challenge for many lies in turning theoretical potential into real business outcomes. Here’s a roadmap to successfully integrating AI into your organization:
1. Focus on Business Value
To successfully leverage AI, prioritize use cases that address key business challenges. The goal of any AI pilot should be to demonstrate measurable business impact, not just technical viability.
2. Leadership is Key
AI implementation must be a company-wide initiative, driven by top leadership. Executives should engage with customers, understand real-world business problems, and work backwards to find AI solutions that scale. Successful AI strategies start from solving critical business needs, not just isolated technical projects.
3. Encourage Innovation by Embracing Failure
Innovation requires risk-taking and accepting occasional failure. Fostering a culture where employees learn from setbacks is crucial to driving AI success. Failure is a step toward innovation—learn fast, adapt, and improve.
4. Fast Prototyping for Rapid Iteration
Success in AI often depends on speed. Develop prototypes quickly, gather feedback, and iterate to create solutions that deliver tangible value to users.
5. Think Big, Start Small
Begin with pilot projects that can deliver significant value, build momentum, and gain buy-in from stakeholders. By starting small, companies can scale their AI efforts effectively over time.
6. Innovate Beyond Internal Use Cases
Avoid limiting AI to internal productivity tools. Instead, focus on using AI to develop new products and services that can open up additional revenue streams and attract new customer segments, driving business growth.
7. Address IP Protection and Data Security Concerns
C-level executives often worry about intellectual property (IP) and data security when adopting AI. However, today’s advanced AI technologies, like large language models (LLMs), offer robust IP protection, ensuring that data access is tightly controlled, even within organizations.
AI’s Role in Private Equity Value Creation
For private equity firms, AI plays a pivotal role in every stage of the investment lifecycle. From identifying risks and opportunities during due diligence to driving value creation and preparing for a successful exit, AI enhances business decision-making by turning data into actionable insights.
To unlock the power of AI to transform your business—start small, think big, and focus on impactful, scalable solutions.
Here is the video of the event:
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