AI Roadmaps and Aftermaths

What defines responsible AI? What is your company’s “AI North Star?” Will AI eventually function more like a colleague, or will it become (gasp!) an overlord?

In a recent webinar, “Creating a Strategic AI Roadmap with Microsoft Generative AI”, AI experts from Argano and Microsoft presented real-world examples and use cases to help businesses in all verticals define and design their own AI strategies.

The high-level takeaways were that AI can and is being used to personalize customer experiences, automate workflows, and unlock creativity. There are no real surprises in what AI is being used for, but there are some surprises in how it is being used.

But. (Yes, a big “but. “) The guidance, even warnings, shared should interest any company beginning its AI journey.

Namely, AI without a unified strategy (a “North Star” guiding its application throughout the enterprise), a system for governance, and user training can create serious issues for the enterprise: data accuracy, data security, and worse.

So, while the webinar experts focused on benefits, they also paid close attention to possible pitfalls and provided a foundational roadmap for the strategic and secure use of Microsoft generative AI.

AI as a path to greater revenue

At its core, AI helps the enterprise discover, unlock, and optimize new efficiencies. The team detailed and demonstrated this by providing examples of how AI enabled staff to focus more on strategic tasks rather than the “grunt work” (which AI could manage).

Microsoft Copilot Studio, which functions as a virtual assistant, is of specific use in this arena. It helps organizations automate endless workflows. (Note that Copilot Studio replaced Microsoft’s earlier, similar application, Power Virtual Agent, which is part of the Power Platform low-code development suite.)

AI-fueled customer engagement

A large part of the webinar centered on how generative AI is transforming the customer experience, both on the customer side (e.g., by helping engage customers with chatbots and self-service tools) and the employee side (e.g., by helping Customer Service Representatives (CSR) enjoy more complete views of every customer and case).

The team dug into how AI can generate new content to improve customer service, leveraging existing FAQs and knowledgebases to create new, more personalized responses to customer inquiries.

There is a critical caveat here as well: in creating new content, most companies will want to put guardrails around how and where generative AI can source material, thereby better ensuring content does not, for example, introduce a competitor or incorrect/inappropriate content or compromise confidentiality. AI can not be allowed to “run free” — it must follow the mentioned North Star.

Generative AI security issues and ideas

When ChatGPT came online, there was no “how-to” guide for it. You could just pump in a question or a task and watch it go. That approach, however, will not work for most companies.

A major takeaway from the presentation was that effective use of AI requires training. One participant even suggested that AI should, in most cases, be isolated, “sandboxed,” to ensure proper handling of confidential data.

Training on proper management of generative AI solutions is a cornerstone of proper governance and is critical to creating a rewarding experience for staff and customers. For any AI rollout, keeping people at the center of the equation remains critical to its strategic application, its effective rollout, and the overall security of your business.

Listen to the whole discussion here, or contact us to get started on your own AI roadmap.