A lot of corporations are turning to AI to stay competitive. What are the biggest advantages this technology brings?
The adoption of AI in corporate settings offers substantial benefits, chiefly in enhancing customer experiences, driving productivity, and reimagining professional work. AI's automation capabilities create new opportunities and necessitate workforce adaptation, allowing professionals to focus on the complex, creative aspects of work. This leads to deeper insights and more personalized services for clients, particularly in fields like law and tax and accounting. AI also augments task delivery, enabling experts to concentrate on their core competencies, while ensuring consistency and quality in work outputs.
Ultimately, when harnessed safely, it has the potential to provide transformative value for organizations and their clients, fostering an environment where human skills are optimally utilized.
What are common challenges for corporations who want to integrate AI into their operations? Which are the hardest to navigate?
First, there is often a change management challenge. Deploying AI solutions often requires the acquisition of new technology and changing a “tried and tested” process or way of doing things in order to produce higher quality results or be more efficient. This change is often difficult and requires training and a learning curve to get over. I encourage organizations to pay that upfront cost because it can pay huge dividends.
Second, there are often issues with data. AI solutions typically work best when they’re powered by data or content that helps them adapt and produce better results. In many organizations, being able to electronically access data in a safe and secure manner can be an impediment to leveraging AI solutions.
To successfully operationalize data across a corporation, organizations need to ensure they're putting ethical considerations upfront in the design and development phases and not as an afterthought. Furthermore, they also need to invest in upskilling employees through company-wide events, custom training resources on AI ethics and access to external training resources.
What advice would you give to engineers building in this space?
When it comes to AI, the advice I have for engineers isn’t much different than the advice I give to others—be curious and learn about new technologies like large language models (e.g. ChatGPT) instead of ignoring them or being scared to work with them. We’re in the midst of a generational technological disruption, and so it’s critical to lean into this tech and get your hands dirty with it. As my colleague and Chief People Officer at Thomson Reuters Mary Alice Vuicic says, when it comes to AI and upskilling, an individual’s AQ—or adaptability quotient—will be just as important as their IQ or their EQ.
What use cases are you most excited about when it comes to machine learning, generative AI and AI in general?
It’s difficult to pick just one—what’s so exciting is that these technologies apply to so many different tasks and functions. However, the general theme I’m excited about is the democratization of knowledge and technology it could enable. Where we can augment deep subject matter experts or process massive amounts of data in an automated way, we can enable many under-served people to access real value. In law, this means you might be able to provide legal advice and help to people who otherwise may be unable to access legal services, helping drive access to justice. In medicine, it might mean that people who aren’t able to access a world-class healthcare system could get some of their needs addressed through technology.
While we need to be mindful of the risks, and navigate those, AI could help us create a much more equitable and inclusive world—which is pretty exciting!
What’s your 10-year forecast for the industry?
The only prediction I can make with confidence in this area is that any prediction I make will be wrong. If you look at how the world has changed from November 2022—when ChatGPT was released—to now, it’s incredible. Not only has AI increased the scale of change, but it’s also increased the pace of that change—so 10 years is an eternity. We’re at the beginning of a wave of innovation that we likely can’t predict, but that’s part of what’s exciting. The most disruptive applications of AI have not yet been written, and I look forward to seeing what they bring!
Shawn Malhotra joined Thomson Reuters in March of 2017 to lead the buildout of a new technology centre. He also served as the Global Head of Open Platform & Eikon as part of the Financial & Risk organization. After the divestiture of the Financial & Risk business, Shawn assumed a role leading technology for the newly formed Corporates Customer Segment in September of 2018. In September of 2020, he was appointed the Head of Engineering for Thomson Reuters. In this role he leads the company’s global Product Engineering teams, delivering solutions in the Legal Professionals, Tax Professionals, and Corporates Customer segments, including 30 years of AI-powered solutions.
To discuss these issues, please contact the author(s).
This publication is a general discussion of certain legal and related developments and should not be relied upon as legal advice. If you require legal advice, we would be pleased to discuss the issues in this publication with you, in the context of your particular circumstances.
For permission to republish this or any other publication, contact Janelle Weed.