Building An Effective AI Strategy

Organizations deploying AI today must recognize that artificial intelligence will originate from multiple sources across the business - not just specialized data science teams. According to Gartner’s latest research, successful AI integration now demands a flexible strategy blending embedded AI, bring-your-own-AI (BYOAI), and enterprise-built AI, all coordinated through robust governance frameworks. 

Embedded AI is rapidly becoming mainstream. Gartner predicts that by 2026, 80% of independent software vendors will have integrated AI features directly into applications like ERP, CRM, and case management tools. Organizations must assess how AI add-ons will enhance or disrupt their existing application portfolios. 

BYOAI reflects the growing trend of business units independently selecting best-of-breed AI solutions to meet specific needs-marketing teams using generative AI for content creation, or legal teams deploying AI for contract drafting. While offering tailored functionality, the accumulation of uncoordinated BYOAI systems risks redundancy, cost overruns, and technical debt if not strategically managed. 

Built and blended AI represents enterprise-driven AI efforts, where internal teams either develop models from scratch or blend external APIs from foundation models with custom integrations. This hybrid approach allows organizations to tailor AI solutions while leveraging the power of massive generative AI models. 

To manage these diverse AI sources securely, IT and AI leaders must embed trust, risk, and security management (TRiSM) practices into their AI frameworks. Smaller enterprises scaling fewer projects may suffice with human-led governance, including ethics committees and AI communities of practice. Larger-scale AI operations, however, will require TRiSM technologies-automated “guardian agents” that enforce AI policies, ensure compliance, and prevent misuse. 

As AI agents and embedded intelligence reshape the enterprise landscape, organizations adopting a coordinated, multi-source AI strategy will be best positioned to drive innovation, minimize risks, and capitalize on AI’s full potential. 

Source:  

https://www.gartner.com/en/articles/deploying-ai