The Build vs. Buy AI Decision Every Marketing Leader Must Make

Organizations are racing to implement AI. But many leaders are finding that building AI in-house is far more complex, costly, and risky than expected.

Successful AI adoption requires specialized talent, governance frameworks, ongoing model maintenance, data infrastructure, security oversight, and continuous adaptation as regulations and technology evolve.  

At the same time, business leaders today are navigating: 

• Rising costs tied to AI development, infrastructure, and ongoing maintenance. 
• Skill gaps and resource constraints that slow deployment and adoption. 
• Increasing regulatory, security, and compliance requirements for enterprise AI initiatives. 
• Pressure to deliver measurable business outcomes and ROI faster than ever. 

This session unpacks the realities behind the Build vs. Buy AI decision — the costs, the risks, the governance requirements, and the long-term considerations every enterprise leader must weigh as they scale AI. 

What you will walk away with 

• A framework for evaluating Build vs. Buy AI decisions within your organization. 
• A clearer understanding of the hidden costs and operational realities of building AI in-house. 
• Insights into governance, compliance, security, and regulatory considerations for enterprise AI deployments. 
• Practical strategies to accelerate speed-to-value while mitigating long-term risk. 
• Examples of how organizations are achieving measurable business outcomes through proven AI solutions. 

The right answer isn't always Build or Buy. It's knowing which one protects your investment for the long run. 

Bring your questions and join the conversation directly with the speakers on the AI challenges and opportunities facing leaders today.