Exploring what’s possible
Right now, you may be examining your business strategies and revising plans for the near and distant future. And as we gradually overcome this crisis, there will undoubtedly be a new normal.
This new normal may require you to examine your business model and to redefine who you are as a company, how you approach problems and how you make decisions. It is an opportunity to think big and be bold – and AI can help. Here are three key considerations as you consider whether and how to become an AI-powered organization:
Scaling AI. To be successful, AI must be woven into the very fabric of your entire organization. AI can have the most impact and make the biggest difference when it is part of your culture and strategy, and when your company’s technological capabilities and desired business outcomes are considered side by side.
Driving AI culture and strategy to move beyond pilot and proof of concept requires the right approach from business leaders. That’s why, more than a year ago, we launched AI Business School, a free online master class series designed to set you up for success. More than a million people have accessed the resources there, and I’m happy to share today that we have added two new modules:
My team and I have had many detailed conversations with AI experts and executives across the world that informed all of the modules, and we will continue to add to the content as we learn more from them about what businesses need for their AI journeys.
To bring AI culture to life, companies are bringing technology and business together into a combined lifecycle driven by business outcomes. This model, which is familiar within software development as DevOps, is making its way into AI development with its counterpart, MLOps. MLOps, known to many as machine learning and operations, can improve business results and accelerate time to market by centrally managing models, environments, code and datasets so they can be shared among data scientists, ML engineers, software developers and other IT teams through the entire ML lifecycle.
In Vancouver, BC, transit agency TransLink deployed 18,000 AI models to better predict bus departure times, accounting for factors including traffic, weather and other disruptions. The agency used MLOps with Azure Machine Learning to manage and deliver the models at such a massive scale that they were able to improve their prediction accuracy by 74% and reduce customer wait times by 50%.
AI for everyone. To fully benefit from AI, each of your employees must feel empowered and included. A recent survey of 10,000 employers and employees found that 91% of employees want new skills that will help them succeed alongside AI. Employees of companies that have integrated AI companywide report that they find more meaning in their work and want to use AI more.
Many of your employees may already be using AI tools in their daily work. AI is incorporated into applications in Microsoft 365 to encourage teamwork, facilitate productivity and improve decision making. And your employees in sales, marketing and customer service may be using solutions in Dynamics 365 AI to improve performance across those departments. In Power Platform, AI Builder gives everyone in your organization the ability to add AI capabilities to the apps they create and use – without any technical experience.
Your organization’s data scientists and developers can use Azure AI services to create custom AI models and applications to solve the unique challenges you face.
One scenario I’m particularly passionate about is the ability for AI to empower subject matter experts. AI for Reasoning enables experts and researchers to choose which AI model to employ to analyze information and easily share it with peers.
Swedish whisky maker Mackmyra recently won a silver cube product design award for creating the world’s first machine-generated whisky. The company’s master blenders fed a machine learning model existing recipes, sales data and customer preferences, and the machine made quick work of generating high-quality recipes that would prove popular.
Swiss pharmaceutical company Novartis used AI to redefine its business functions across the organization, empowering every individual to apply AI models to augment their expertise and creativity without needing to learn data science. AI brought together mass amounts of critical information across data sources and streamlined collaboration.
Now, 50,000-plus employees can quickly make sense of the vast amount of data they deal with, deriving insights that will help them transform how medicines are discovered, manufactured and commercialized.
Responsible AI. As you put AI into action, particularly in these times of change, it’s imperative to consider the implications of technology. AI must be integrated in a way that aligns with your company’s values, goals and priorities. Companies that incorporate AI successfully implement practices from the beginning to guard against potential misuse of AI, such as biased or unfair results.
At Microsoft, we’ve been on our own AI journey for some time, and we are committed to sharing key learnings and are doing so both through the Responsible AI module within our AI Business School as well as the Responsible AI Resource Center, which is perfect for technical teams developing and deploying AI.
How can we help?
We know you’ve got a tremendous amount on your plate right now. Considering how you adjust to the changes we’re all experiencing, while continuing to serve your customers and support your employees, is an extremely tall order. As difficult as the current challenges are, we believe the implementation of short-term solutions and a focus on strategic, long-term planning go hand in hand as you transform your company into an AI-powered organization. Now is a perfect time to think of the possibilities. Good ideas coupled with perseverance will go a long way toward helping you respond to today’s challenges and imagine a better tomorrow. We’re excited to help you as you make progress on your AI journey. Visit AI Business School to help you get started putting AI into action. I promise, you’ll be glad you did.