Artificial intelligence is a kind of catalyst; it’s the next wave of truly transformative technology with potential we cannot yet fully envision or appreciate. Companies will start by using this new technology to do “old things” before discovering the new opportunities it creates. So, how should they go about this process? They should: start by experimenting, deploy for productivity, transform experiences, and then try to build new things. Throughout this process, they should prioritize security and responsible use.
Recently, like millions of people, I used a ride-sharing app on my smartphone. It was pretty uneventful and not something I gave much thought. Ride-sharing is simple and convenient, and it’s now an $80+ billion industry. But it wasn’t that long ago that it didn’t even exist. We had cars, we had riders, and we had drivers; but to work, ride-sharing needed smartphones. When they arrived, so did an enormous variety of conveniences and new experiences — some that became entire industries — that we never could have imagined.
Artificial intelligence is a similar kind of catalyst; it’s the next wave of truly transformative technology with potential we cannot yet fully envision or appreciate. It is the defining technology of our time, changing the way we live and work. In my entire career in tech, I’ve never been more excited and optimistic than I am now. I have a colleague at Microsoft who talks about AI like this: You’ve got to use the “new thing” to do old things better. Then, you use the new thing to … do new things. He’s right.
Consider an example from health care. Paige is a software company using AI to change the way doctors identify, diagnose, and treat cancers. With properly trained and tuned models, AI can look at thousands of digital pathology images, pixel by pixel, and detect abnormalities faster and with more accuracy. Imagine what these tools can unlock not only for pathologists and doctors, but for patients, too. It means earlier disease detection, healthier lives, and more time with loved ones.
Right now every company, no matter the size or industry, should be thinking about AI. AI is moving from its auto-pilot phase, which was all about narrow, purpose-built tools that use machine learning models to make predictions, recommendations, and automate, to its copilot phase, where there’s tremendous opportunity to revolutionize how just about everything gets done. Leaders who embrace AI now and take action to understand it, experiment with it, and envision how it can solve hard problems are going to run companies that thrive in an AI world.
But where should they start? Nearly every day, I talk with business leaders who ask important questions about AI’s potential. No matter where you are in your AI journey, it’s incumbent upon every leader to embrace this unique time and take advantage of this powerful technology. If you feel unsure how to start, or how to move forward, you’re not alone. Like any business-planning exercise, think about your AI strategy in phases. Embrace agility and change, and keep a continuous learning mindset, calibrating and adjusting your gameplan as you go.
Start by Experimenting
The best way to learn about AI is to use it. It’s rare for new and disruptive technology to be immediately accessible. This is. Most of the leaders I talk with have tried popular AI applications like ChatGPT or the new Bing. There are many other options out there, but the point is to get curious.
Try applying it to whatever task is in front of you and see what it’s good at and what it’s not. Use it to generate interview questions, write a memo, research and summarize a topic you want to learn more about, or get thought starters for a document. I used Bing and ChatGPT to help me get ideas for a speech. I’ve used Microsoft 365 Copilot, the AI integration across Microsoft apps to generate slides, to find and summarize documents that share a topic, and to recap email exchanges with colleagues. By using and experimenting with AI, you’ll be in a better position to imagine how it could be used in your organization — and you likely know better than anyone where opportunities and potential exist.
Deploy for Productivity
When it comes to productivity, AI copilots — from Microsoft and from others — can be deployed or embedded in applications to assist or simplify certain tasks. Less than two years since its launch, GitHub’s Copilot is already writing 46% of the code on its repository and helps developers code up to 55% faster. Imagine what developers are doing with that extra time. Three out of four users say it helps them conserve mental energy and focus on more satisfying work. Said another way: Creating new things and solving new problems.
Consider the workflows and process-driven activities in your business: things like payroll, on-boarding, or IT help desk support. These are all repeatable, rules-based processes that can be streamlined with AI. This is the driver behind an entire new category of AI software that can handle manual tasks and reshape scores of business processes.
There’s another way to think about AI for productivity: time. If you’re in fraud detection, or you’re a security analyst, time can be your biggest asset or your biggest challenge. If you can shorten the amount of time it takes to comb through lots of data-rich, time-sensitive information, you’re already better and more effective at your job.
Today, AI is already impacting how businesses deliver experiences that are better, faster, more efficient, or entirely new, from predictive text on your phone to chatbots on websites to suggested searches when you open a browser.
As an example, PwC is using Azure OpenAI Service to expand and scale its own AI offerings while also helping clients in industries like insurance or healthcare reimagine their businesses by leveraging the power of generative AI. CarMax is using it to analyze hundreds of thousands of customer reviews and surface key takeaways for buyers about every make, model, and year of vehicle in its inventory.
Even in its early stages, AI is making employee experiences better too. A recent Microsoft survey found that 89% of employees and business decision makers with access to automation and AI-powered tools feel more fulfilled. They say it’s because they can spend time on work that truly matters. Nine out of 10 said they want the opportunity to apply AI solutions to even more tasks and activities.
I see that happening already in some of the organizations I work with. They’re pursuing more advanced AI in use cases like customer support, writing assistance, or data extraction and classification. The common thread in each of these involves using AI to leverage resources or information you already have to transform experiences for people.
Build New Things
The above steps are versions of using the “new thing” to do old things better, to borrow my colleague’s turn of phrase. But how can you use the new thing to actually do new things? What can you do that’s completely different? How can you delight customers and create new lines of business and, with them, new revenue?
This is the challenge before business leaders right now; and it’s a hard one. The answer starts with integrating AI into your organization and iterating from there. Because while AI will enable people and organizations to achieve more, we’re at the very beginning of defining what “more” looks like. But to move ahead, we need to put in place the conditions that we help us discover what comes next.
One of the really exciting things about using AI to be more efficient — whether that’s using generative AI to get ideas or to conduct research — is that it allows you to think more deeply about a concept or a problem you’re trying to solve. It’s not a far leap to imagine how this level of concentrated effort is going to enable companies to develop truly new and innovative solutions faster; and then take advantage of the snowball effect of that speed.
Throughout: Prioritize Security & Responsible AI
Alongside all of AI’s promise, one thing is certain. We will not realize AI’s full potential without safeguards. Technology has always been an accelerator and an enabler. AI is no different, but it does present potential risks that have to be managed.
For any company, the success of Responsible AI initiatives depends on at least three things. First, it takes committed and involved leadership. (Microsoft’s Vice Chair and President, Brad Smith, and our Chief Technology Officer, Kevin Scott, chair our Responsible AI Council.) Second, companies must build inclusive governance models and actionable guidelines, as we have done. Finally, they must also invest in responsible AI in the form of new engineering systems, incubations that are research-led, and in the people who will ensure that responsible AI principles are put into practice. At Microsoft, we have hundreds of people working on this, and for many of them, it’s their full-time job. Beyond that, we’ve adopted the mindset that using AI responsibly is a responsibility we all share, no matter your role.
The AI roadmap will be different for every organization, and it looks different depending on whether you’re a tech company or not. Tech companies are more likely to have already implemented some form of intelligent agent into their software experiences, for example. But for everyone, the potential is massive, and the time to start is now.
Just like ride-sharing needed smartphones, there are as-yet conceived industries that will need AI to get off the ground. Most of us recognize that AI will be completely game-changing. We see the practical applications — not only for the tech landscape but for humanity, and that’s what’s truly profound about this.
The AI market is moving quickly, and the cycles in and around AI are faster than we’ve ever seen. Right now, there is tremendous opportunity for business leaders to embrace AI and adapt to the profound changes that are coming. There is exponentially greater opportunity for the businesses that use AI to lead and drive that change.
By Christopher Young July,2023- Harvard Business Review