Too many AI options. Too few results. A decision map for engineering leaders.
How to cut through the AI noise, map the landscape, and match the right AI solutions to your strategy.
Details
As an engineering leader, you know AI belongs in your engineering stack. Yet you're stuck in decision paralysis. Unsure which AI platforms fit, and why the ones you've tried haven't delivered what the pitch promised.
The AI market is loud, crowded, and hard to read. This webinar is your Gordon Ramsay — cutting the AI menu down to what actually works.
Join a Capgemini EVP, an AI-enabled manufacturing leader, and two Synera experts as they talk candidly about how to unstick your adoption of AI for engineering. You'll walk away with a clearer view of which AI investment speeds up how your team competes, and vendor evaluation questions worth asking.
Your Key Takeaways
- Capgemini EVP Praveen Cherian's core vs context distinction to decide which work is safe to hand to an AI agent and which stays with a person
- AI leader Dr. David Panni’s adoption methodology of starting with tasks that are small enough to succeed past your pilot
- DIY vs Buy Comparison to understand the trade-offs, AI Value Assessment to evaluate agentic impact, and other Decision Maps to use right away
Who It's For
- C-Level executives seeking validation that their team is moving toward the right AI investment
- VP / SVP Application Engineering looking to cut through the AI noise and make a confident platform decision
- R&D and Engineering Leaders evaluating which AI solutions actually fit their stack and deliver on the pitch
Teaser:
Our partner
Capgemini
Capgemini helps businesses imagine their future and make it real with AI, technology and people. As a leading advisor and transformation partner to companies around the world, we have leveraged technology to enable business transformation for almost 60 years. We address the entire breadth of business needs, from strategy and design to managing operations and engineering. Drawing on deep industry knowledge and technical expertise in cloud, data, artificial intelligence, connectivity, software, digital engineering, and platforms.



