by Catherine Amirfar, Megan Bannigan, Charu A. Chandrasekhar, and Karen Levy
Left to Proper: Catherine Amirfar, Megan Bannigan, Charu A. Chandrasekhar and Karen Levy (images courtesy of Debevoise & Plimpton LLP)
As we glance again on 2025, one theme that emerges from our work serving to over 100 shoppers with their AI adoption is that extracting actual worth from AI takes a sustained effort throughout the group, and people investments at the moment are beginning to repay.
In 2026, we anticipate that many companies will emerge from the pilot/experimentation AI section and transition to an operational section that features a number of large-scale AI use instances in manufacturing, with demonstrable ROI within the type of both value financial savings or new sources of income.
These companies will probably have gone via lengthy intervals of abilities constructing, governance enhancements, pilot applications, mannequin testing, and use case iteration, with many small victories and failures alongside the lengthy highway to determining how AI can ship actual worth for his or her explicit companies.
That funding of time was wanted to align enterprise technique with AI technique and to seek out the suitable mixture of instruments, expertise, workflows, pilot applications, coaching, and governance essential to implement high-value/low danger AI use instances at scale.
These companies at the moment are positioned to broaden the scope of their extra profitable use instances, and to rapidly discover and implement new priceless use instances, which results in a compounding and accelerating benefit loop.
In our expertise, each at Debevoise and with our shoppers, AI success results in extra AI success, together with elevated buy-in from workers and administration, higher understanding of what AI instruments can and can’t do, and extra concepts for how one can use AI to avoid wasting money and time or ship solely new providers to shoppers.
By way of this course of, workers develop their AI abilities, enhance present use instances, and speed up the timeline for transferring new ones into manufacturing, creating much more organizational momentum. These companies which are forward now will discover it comparatively simple to remain forward, particularly if they’ll poach expertise from the companies which have fallen behind.
For these corporations that discover themselves behind in AI adoption, it’s actually not too late to catch up. Certainly, the trail to success is clearer now that it was a yr in the past, so it ought to take much less time to succeed in profitable adoption than it did in 2025, however these which are forward are gaining momentum. So, for most of the corporations which have largely been on the AI adoption sidelines, the time to get within the sport is now.
Catherine Amirfar, Megan Bannigan, and Charu A. Chandrasekhar are Companions and Karen Levy is the Chief Data Officer at Debevoise & Plimpton LLP.
The views, opinions and positions expressed inside all posts are these of the writer(s) alone and don’t signify these of the Program on Company Compliance and Enforcement (PCCE) or of the New York College Faculty of Legislation. PCCE makes no representations as to the accuracy, completeness and validity or any statements made on this website and won’t be liable any errors, omissions or representations. The copyright of this content material belongs to the writer(s) and any legal responsibility as regards to infringement of mental property rights stays with the writer(s).
by Catherine Amirfar, Megan Bannigan, Charu A. Chandrasekhar, and Karen Levy
Left to Proper: Catherine Amirfar, Megan Bannigan, Charu A. Chandrasekhar and Karen Levy (images courtesy of Debevoise & Plimpton LLP)
As we glance again on 2025, one theme that emerges from our work serving to over 100 shoppers with their AI adoption is that extracting actual worth from AI takes a sustained effort throughout the group, and people investments at the moment are beginning to repay.
In 2026, we anticipate that many companies will emerge from the pilot/experimentation AI section and transition to an operational section that features a number of large-scale AI use instances in manufacturing, with demonstrable ROI within the type of both value financial savings or new sources of income.
These companies will probably have gone via lengthy intervals of abilities constructing, governance enhancements, pilot applications, mannequin testing, and use case iteration, with many small victories and failures alongside the lengthy highway to determining how AI can ship actual worth for his or her explicit companies.
That funding of time was wanted to align enterprise technique with AI technique and to seek out the suitable mixture of instruments, expertise, workflows, pilot applications, coaching, and governance essential to implement high-value/low danger AI use instances at scale.
These companies at the moment are positioned to broaden the scope of their extra profitable use instances, and to rapidly discover and implement new priceless use instances, which results in a compounding and accelerating benefit loop.
In our expertise, each at Debevoise and with our shoppers, AI success results in extra AI success, together with elevated buy-in from workers and administration, higher understanding of what AI instruments can and can’t do, and extra concepts for how one can use AI to avoid wasting money and time or ship solely new providers to shoppers.
By way of this course of, workers develop their AI abilities, enhance present use instances, and speed up the timeline for transferring new ones into manufacturing, creating much more organizational momentum. These companies which are forward now will discover it comparatively simple to remain forward, particularly if they’ll poach expertise from the companies which have fallen behind.
For these corporations that discover themselves behind in AI adoption, it’s actually not too late to catch up. Certainly, the trail to success is clearer now that it was a yr in the past, so it ought to take much less time to succeed in profitable adoption than it did in 2025, however these which are forward are gaining momentum. So, for most of the corporations which have largely been on the AI adoption sidelines, the time to get within the sport is now.
Catherine Amirfar, Megan Bannigan, and Charu A. Chandrasekhar are Companions and Karen Levy is the Chief Data Officer at Debevoise & Plimpton LLP.
The views, opinions and positions expressed inside all posts are these of the writer(s) alone and don’t signify these of the Program on Company Compliance and Enforcement (PCCE) or of the New York College Faculty of Legislation. PCCE makes no representations as to the accuracy, completeness and validity or any statements made on this website and won’t be liable any errors, omissions or representations. The copyright of this content material belongs to the writer(s) and any legal responsibility as regards to infringement of mental property rights stays with the writer(s).
