Why User-Adoption and Training Are Central to AI Growth

History has a way of repeating itself...

Years ago, when unified communications (UC) solutions were gaining traction, I recognized the important role of end-user adoption, utilization, and training.

I dedicated substantial time to writing, speaking, and conducting research on this critical aspect, recognizing its pivotal role in driving the success of UC deployments. In 2020, Kevin Kieller and I conducted a BCStrategies study surveying end users to understand the impact of training and adoption on the use of unified communications and collaboration (UCC) tools.

Fast forward to today's rapidly evolving artificial intelligence (AI) landscape, particularly generative AI tools such as copilots, assistants, and large language models (LLMs). Once again, the spotlight falls on user adoption and training as the linchpin for organizations seeking to unlock the full potential of these cutting-edge technologies.

Adoption Doesn't Happen Spontaneously

When questioning vendors about their approach to facilitating user adoption and training for AI solutions, most respond that their tools are intuitive and require minimal guidance, expecting adoption to occur organically.

This was similarly said about UCC technologies, yet our BCStrategies survey revealed otherwise. Key findings of that study include:

• Two-thirds of users who received adequate initial training found UCC solutions enhanced their productivity, whereas none of the inadequately trained users reported the same.
• Nearly three-quarters of users believed additional UCC training would enhance their effectiveness.
• Organizations that marketed and promoted new UCC solutions internally before deployment saw higher adoption rates than those that did not.

The study showed that to maximize the benefits of UCC systems, organizations must invest in comprehensive user adoption and ongoing training programs. The same approach is essential for AI and generative AI technologies.

Mastering the Art of Prompting

Prompts are fundamental for generative AI, serving as the instructions users provide, typically in natural language. Prompt engineering involves refining these instructions to achieve optimal results. However, most users are not skilled in prompt engineering and crafting effective prompts. 

The recent Enterprise Connect keynotes showcased generative AI copilots and assistants, with demos highlighting the AI's capabilities in summarizing interactions, creating charts and graphs, building project plans, drafting and refining emails, and more.

I kept thinking to myself: "This is impressive, but how will end-users know what to ask these AI copilots and assistants?" 

While some vendors offer prompt templates to guide users, harnessing the power of these AI assistants requires more comprehensive training.

End-users must understand what they can ask the AI to do and how to phrase their instructions and prompts effectively.

In addition, training on ensuring personal and corporate privacy and security when engaging with generative AI is crucial to prevent inadvertent disclosure of sensitive information.

Vendors Need to Provide Assistance

To maximize their AI investments, organizations must equip end-users with a clear understanding of the AI's capabilities and limitations, as well as best practices for getting the desired results.

While simple tasks like summarizing meetings or drafting chat responses may not require extensive training, more complex functions require guidance on creating effective prompts and adhering to security protocols.

I encourage all vendors offering AI solutions, particularly generative AI, to prioritize end-user usage, adoption, and training. And I encourage all business users to ask their vendors about what kind of adoption and training tools are available to help encourage the effective usage of AI solutions.

This will help customers realize the full benefits and return on investment from their AI solutions while promoting security, privacy, and compliance best practices.