Agentic AI: Why CIOs Are Opting to Buy Instead of Build
Because of the complexity and high risk of building internal AI solutions, CIOs are increasingly opting to buy them from specialized providers.
New mobile apps to keep an eye on
Hendrerit enim egestas hac eu aliquam mauris at viverra id mi eget faucibus sagittis, volutpat placerat viverra ut metus velit, velegestas pretium sollicitudin rhoncus ullamcorper ullamcorper venenatis sed vestibulum eu quam pellentesque aliquet tellus integer curabitur pharetra integer et ipsum nunc et facilisis etiam vulputate blandit ultrices est lectus eget urna, non sed lacus tortor etamet sed sagittis id porttitor parturient posuere.
- Lorem ipsum dolor sit amet consectetur rhoncus ullamcorper ullamcorper
- Mauris aliquet faucibus iaculis dui vitae ullamco
- Posuere enim mi pharetra neque proin vulputate blandit ultrices
- Posuere enim mi pharetra neque  pellentesque aliquet tellus proindi
What new social media mobile apps are available in 2023?
Sollicitudin rhoncus ullamcorper ullamcorper venenatis sed vestibulum eu quam pellentesque aliquet tellus integer curabitur pharetra integer et ipsum nunc et facilisis etiam vulputate blandit ultrices est lectus vulputate eget urna, non sed lacus tortor etamet sed sagittis id porttitor parturient posuere.
Use new social media apps as marketing funnels
Eget lorem dolor sed viverra ipsum nunc aliquet bibendum felis donec et odio pellentesque diam volutpat commodo sed egestas aliquam sem fringilla ut morbi tincidunt augue interdum velit euismod eu tincidunt tortor aliquam nulla facilisi aenean sed adipiscing diam donec adipiscing ut lectus arcu bibendum at varius vel pharetra nibh venenatis cras sed felis eget.
- Lorem ipsum dolor sit amet consectetur fringilla ut morbi tincidunt.
- Mauris aliquet faucibus iaculis dui vitae ullamco neque proin vulputate interdum.
- Posuere enim mi pharetra neque proin  bibendum felis donec et odio.
- Posuere enim mi pharetra neque proin aliquam mauris at viverra id mi eget.
“Eget lorem dolor sed viverra ipsum nunc aliquet bibendum felis donec et odio pellentesque diam volutpat.”
Try out Twitter Spaces or Clubhouse on iPhone
Nisi quis eleifend quam adipiscing vitae aliquet bibendum enim facilisis gravida neque velit euismod in pellentesque massa placerat volutpat lacus laoreet non curabitur gravida odio aenean sed adipiscing diam donec adipiscing tristique risus amet est placerat in egestas erat imperdiet sed euismod nisi.
What app are you currently experimenting on?
Eget lorem dolor sed viverra ipsum nunc aliquet bibendum felis donec et odio pellentesque diam volutpat commodo sed egestas aliquam sem fringilla ut morbi tincidunt augue interdum velit euismod eu tincidunt tortor aliquam nulla facilisi aenean sed adipiscing diam donec adipiscing ut lectus arcu bibendum at varius vel pharetra nibh venenatis cras sed felis eget.
AI is no longer a “nice-to-have” for SaaS enterprises. It’s now expected to power go-to-market (GTM) strategies, drive Revenue Operations (RevOps), and deliver real results—like reducing churn, scoring leads, and improving revenue forecasts.
But there’s a growing realization among tech leaders: building internal AI is harder than it looks. And for most organizations, it’s not the smartest path forward.
That’s why a growing number of CIOs are making a strategic shift: instead of building internal AI solutions, they’re buying them from specialized providers.
Internal AI Projects: High Stakes, Low Success Rate
Over 70% of enterprise AI projects fail to deliver meaningful outcomes. Most never make it to production. And the reasons are well documented: fragmented data, lack of productization, unclear ownership, poor adoption, and rising complexity as new tools like large language models (LLMs) enter the mix.
These aren’t just minor hurdles. For most enterprises, these are fundamental capability gaps—requiring mature data infrastructure, highly specialized talent, and cross-functional execution at scale.
And the cost of getting it wrong is significant: wasted resources, delayed GTM optimization, and reduced stakeholder trust in AI initiatives.
Why “Buy” Is Becoming the Smarter Move
According to a Salesforce survey, only 11% of CIOs at large enterprises have fully implemented AI, despite overwhelming belief in its transformative potential. Security, data complexity, and infrastructure concerns were among the top blockers.
This aligns with broader industry research showing that CIOs are increasingly turning to external AI providers—both cloud and niche—for model development, orchestration, and integration. These partners offer a clear advantage:
- Speed to deployment with prebuilt models and ready-made integrations
- Domain expertise from working across multiple customers and use cases
- Cost efficiency by avoiding the need to build full in-house AI infrastructure
- Operational maturity with built-in compliance, observability, and lifecycle support
In fact, CIO.com reports that many enterprises are now bypassing the big cloud providers in favor of smaller, more specialized AI vendors who can move faster and offer tailored services.
The Hidden Cost of Building AI In-House
Building internal AI capabilities isn't just about hiring a few data scientists. It requires:
- A modern, scalable, and governed data stack
- Skilled ML and MLOps engineers
- Deep RevOps domain knowledge
- Legal and compliance oversight
- Long-term maintenance and retraining capabilities
Most CIOs find that by the time they’ve assembled the team, built the infrastructure, cleaned the data, and integrated the outputs, months—or even years—have passed. Meanwhile, competitors using prebuilt solutions are already acting on insights and improving revenue outcomes.
What This Means for CIOs
The question CIOs must ask today isn’t just “Can we build this?” It’s “Should we build this?”
In many cases, the answer is no.
Buying purpose-built AI solutions allows CIOs to shift their focus from technology execution to business impact. It frees teams from low-level model management and lets them concentrate on aligning intelligence with GTM priorities.
And most importantly, it increases the odds of success—by delivering faster time to value, higher adoption, and proven, scalable intelligence.
AI success isn’t about how much code you write—it’s about how much value you deliver. For most SaaS enterprises, that means buying smarter, not building harder.
