Shaping the AI conversation
Thanks to James Byun for the invitation to participate in this great panel! Photo credit Erica Hall.

Shaping the AI conversation

The most important thing I do is meet with our customers – it’s one of the highlights of my job.

In those meetings, no matter who’s in the room or what’s on the agenda, there’s one topic we almost always come back to: The importance of their data estate and potential opportunities for Machine Learning and Artificial Intelligence in their business

We don’t always call it that, and we’re certainly not talking specifics about machine learning algorithms or bot frameworks. But one way or another, customers want to know how to inject more intelligence into their business processes to drive more intelligent business outcomes.

I recently had the opportunity to connect with Microsoft’s AI Ambassadors in the US. They’re the front lines for AI in the US field, educating customers, partners, and developers about the possibilities unlocked by AI and helping customers on their journey toward digital transformation.

They’ve seen some amazing innovations and brought us insightful feedback, and I wanted to share some of the thoughts I took away from my time connecting with them.

The AI conversation always begins with data.

Data is at the core of how today’s companies drive growth, and there are three key steps to maximizing the strategic impact of your data: Accessibility, Prediction, and Automation.

First, you need to get your data online and accessible, with a single source a truth. Establishing a modern data estate is the most critical step because clean, accessible data will amplify the impact of AI.

From there, you can move into prediction, leveraging machine learning, predictive analytics, and advanced services to generate forward-looking insights to inform decision-making.

That brings you to the end goal: Automation. Through the power of data and AI, automation can significantly transform how you empower employees, engage customers, and optimize operations. Increasingly in my conversations with customers, we frequently explore automation use cases and scenarios due to its potential for transformative impact.

But AI doesn’t mean you’re absolved from decision making.

A few weeks ago, a customer told me a story of an early AI project they were incredibly excited to implement. But after a few months online, they realized that their outcomes weren’t improving as expected, and they weren’t seeing the benefits they’d hoped for.

Much of this was rooted in the lack of a clean, modern data estate – the first step on the data journey – but it was exacerbated by an AI model that was built using faulty assumptions and decision principles.

When you’re looking at bringing AI capabilities into your business, it is important to apply intelligent and fair decision principles to ensure that your model is delivering insightful, non-biased results. Additionally, transparency into how the AI model is working is equally important, allowing you to understand why or how you arrived at a specific outcome. 

The foundation for AI must be strong.

The advanced capabilities and innovative scenarios presented by AI are certainly compelling. However, your ability to advance those projects comes back to a solid foundation.

You need a plan for security that addresses the risk factors specific to your industry – AI on an oilfield presents different risks than AI in a retail store. You need defined policies around privacy and personal data that considers local and international regulation. And you need to recognize the human element of any AI endeavor, whether that’s a regular ethics review to ensure fair and non-biased results or a reskilling program to ensure your team has the capabilities they’ll need to succeed long-term.

For Microsoft, that essential foundation is our Responsible AI approach that defines how we assess the risks, societal impact, and other key issues associated with applying AI. Responsible AI consists of six principles: Fairness, transparency, reliability and safety, privacy & security, inclusiveness, and accountability. We believe these principles will ensure the innovation made possible by AI has a positive impact on the world around us, and I’m proud of Microsoft’s leading role in this space.


AI has the potential to reshape nearly every industry on the planet. Teams like Microsoft’s AI Ambassadors will be leading the way for that transformation with their thoughtful approach, passion for innovation, and drive to see customers succeed. I’m so excited to be part of the future they’ll envision.

Christine Zagielski

Managing Director, Azure@Microsoft US Health and Life Sciences

5 年

Thanks for sharing Phil Sorgen I especially appreciate Microsoft’s definition of Responsible AI consisting of six principles: Fairness, transparency, reliability and safety, privacy & security, inclusiveness, and accountability.

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Our learning is to getting your data ready for AI is critical first step to realize benefits and enable machine learning to be effective.?

Justin Fletcher

Global Client Director at Microsoft

5 年

Great share, Phil, thanks - Can't emphasize enough the need for 'clean, accessible data' in order to reap benefits from AI

Henry Gleditsch Kleive

Director Business Development, MBA, author

5 年

Thanks for your insights!

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Mike Courtney

Digital & Artificial Intelligence Solutions Leader

5 年

Really clear and key points from Phil Sorgen on #AI and how Microsoft is being a champion for #ethicalAI

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