Despite the hype, LinkedIn found that third-party AI tools for coding and design don't work out-of-the-box on their complex, legacy stack. Success requires deep customization, re-architecting internal platforms for AI reasoning, and working in "alpha mode" with vendors to adapt their tools.

Most companies are not Vanguard tech firms. Rather than pursuing speculative, high-failure-rate AI projects, small and medium-sized businesses will see a faster and more reliable ROI by using existing AI tools to automate tedious, routine internal processes.

The biggest hurdle for enterprise AI adoption is uncertainty. A dedicated "lab" environment allows brands to experiment safely with partners like Microsoft. This lets them pressure-test AI applications, fine-tune models on their data, and build confidence before deploying at scale, addressing fears of losing control over data and brand voice.

AI agent platforms are typically priced by usage, not seats, making initial costs low. Instead of a top-down mandate for one tool, leaders should encourage teams to expense and experiment with several options. The best solution for the team will emerge organically through use.

The true enterprise value of AI lies not in consuming third-party models, but in building internal capabilities to diffuse intelligence throughout the organization. This means creating proprietary "AI factories" rather than just using external tools and admiring others' success.

Instead of guessing where AI can help, use AI itself as a consultant. Detail your daily workflows, tasks, and existing tools in a prompt, and ask it to generate an "opportunity map." This meta-approach lets AI identify the highest-impact areas for its own implementation.

To balance security with agility, enterprises should run two AI tracks. Let the CIO's office develop secure, custom models for sensitive data while simultaneously empowering business units like marketing to use approved, low-risk SaaS AI tools to maintain momentum and drive immediate value.

Since Microsoft is a primary partner for OpenAI, its published guidelines for making content AI-friendly (e.g., using Q&A blocks, simple tables) are a direct feeder for what gets surfaced in ChatGPT. Marketers should follow Microsoft's rules to optimize for all major AI tools, not just Microsoft's.

Instead of being swayed by new AI tools, business owners should first analyze their own processes to find inefficiencies. This allows them to select a specific tool that solves a real problem, thereby avoiding added complexity and ensuring a genuine return on investment.