Why organizations need an AI adoption framework

This episode is sponsored by Mazars USA.   As Microsoft and other large technology firms accelerate their AI-related roadmaps, businesses have no choice but to reckon with how different technology will impact their employees, customers, and partners. Some AI tools will be relatively easy to deploy, like prebuilt capabilities coming to Microsoft Dynamics 365 apps via Copilot. Other uses of AI will require greater investment, carry different risk profiles, and raise new ethical, regulatory, and governance question.    Ivan Cole, managing director at Mazars USA about AI adoption in the Microsoft space, joins us to these topics and expand on some of the points he and his colleague, Microsoft MVP Chris Segurado, raised in a recent webcast for the MSDW audience about adoption and momentum of AI in the Dynamics space.   As Ivan explains, all artificial intelligence isn’t created equal. With the popularity of generative AI, we are seeing a tendency for people to confuse it with other capabilities like machine learning (ML) and natural language processing (NLP). Ivan explains how he untangles some of these fundamentals and shares his outlook on why an AI framework helps guide businesses in their approach to the various technologies.   Show Notes: 2:30 - What do people understand well about AI today and where do they need education? 6:00 - How to harness an organization's enthusiasm to take advantage of AI capabililties in the Microsoft space 12:30 - How AI's implementation could change specific roles in organizations 16:00 - Looking for AI solutions that extend beyond what Microsoft offers out of the box 18:30 - What it means to enable security and guardrails for AI adoption 22:00 - Why organizations need to make rapid progress on their AI governance policies   More from Mazars: With Mazars' SAFE AI FrameworkTM as your guide, you can confidently embrace your organization’s future with AI. Journey with Mazars and discover AI's enormous potential, while ensuring its use aligns with best practices for security, adaptability, factual integrity and ethics. Learn more about SAFE AI Framework.