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A Look Ahead in IT Automation

Kenneth Adler is Chair of Loeb & Loeb LLP’s Technology & Sourcing practice group and maintains a practice focused on complex global and domestic outsourcing and technology-enabled transactions. For more than 30 years, he has served as a trusted advisor to a wide range of clients on all aspects of information technology and business process outsourcing transactions, ranging in size from several million dollars to several billion. He also has significant experience addressing the creation of, and strategies relating to, cloud computing and other new technologies, including the emerging area of robotics process automation and IT automation. 

What’s the one development in the technology space that you think is going to have the biggest impact in the next three to five years?

The biggest new development is IT automation, which is having a significant impact as an innovative and disruptive technology. A lot of people think of it only as “artificial intelligence,” but that’s a misnomer. AI, in the sense of a pure, cognitive thinking solution, is probably not yet as fully developed as most might think. However, different types of solutions are emerging and being implemented, all of which somewhat fall into what people might call AI. I’d say there’s a “continuum” when we look at the technology.

The first part of this continuum is RPA, or robotics process automation, which includes things like smart software or “bots” that follow rules-based programming to perform routine, defined tasks. Essentially, RPA can be implemented to do tasks performed by a human which are repetitive in nature, by putting all of the decision-making processes into a smart software. Think about automating routine back-office functions such as issuing purchase orders or invoices, or automating call center work, where increasingly you’re being directed to automated menus and often working out the solution to your problem without speaking to a real person. These, and other examples of RPA, allow the work to be done on an automated basis rather than having an individual complete a task. Sometimes, tasks and workflows can be divided up between an RPA tool and a human so that companies can capture cost savings and free up employees to perform more high-level work.

Beyond RPA is machine learning, which involves building algorithms to have a computer perform a particular task through analysis, understanding and identification of patterns in data. This differs from RPA since this is not simply performing rules-based tasks. The machine will analyze the data and learn by recognizing patterns in the data, and through repeat usage, it will rely on those patterns and inference to learn how to complete the task. Current examples of machine learning include speech and facial recognition and fraud detection in credit card processing.

The next level is the concept of AI. Many times, machine learning is included within what the industry calls “AI,” but AI also includes “deep learning” and other analytical results, not simply replicating a string of tests. Consider the use of AI to assist the health care industry in disease detection, diagnosis and treatment, or proactive healthcare management, or in the financial services industry to perform automated financial portfolio planning.

What makes Loeb a leader in this space? 

Loeb stands out in this space because we have a dedicated practice that advises clients on IT sourcing and contracting, whereas many firms group this in with their intellectual property or corporate practices. Collectively, our team has decades of experience in the technology and sourcing space, and most of our attorneys have spent their entire careers focused on some aspect of technology and sourcing transactions. By virtue of practicing in this space for so long, we’ve watched the industry go through and seen our clients through times of innovation and disruption. So, we’ve not only worked on virtually every type of deal, but we can also offer strong perspectives on what more forward-looking innovations, like RPA, machine learning and AI, mean for business. We leverage our vast learnings and experience to address the risks of contracting for development and implementation of new technologies. In fact, we are already advising our clients on many of these IT automation issues – clients who are early adopters.

McKinsey and Company conducted a 2019 survey called the “Global AI Survey: AI proves its worth, but few scale impact.” More than half of respondents said their organization has embedded at least one AI capability into a process or product. What is your perspective – is AI becoming mainstream? 

If you are looking at AI and are including RPA, I think there is increased adoption of these technologies. More companies are going beyond just dipping their toes in the water and are actually implementing some form of IT automation, either in their own data centers or through a third-party hosted solution or service. There’s a lot of debate in the industry about which types of AI technologies will survive. Right now, there is a lot of buzz around RPA, though it is generally accepted that there will be a shift toward implementing more complex types of AI in the near future, which may be combinations of RPA and AI.

Presently, we are seeing implementation across many industries. Our clients, who are mainly in the financial services, insurance, health care and retail services industries, include some form of IT automation among their yearly initiatives. Our colleagues in Loeb’s Advanced Media and Technology practice see it being implemented in many other industries, as well. So we think the trend toward implementing these solutions on a wider basis has been consistent and that we can expect to see more and more businesses get on board. 

What are some of the challenges to companies doing these deals?

There are new risks associated with implementing IT automation, and we can help our clients assess these risks. As the technology advances, these deals are becoming much more multifaceted, implicating new areas of law and compliance risks. For example, the shifting landscape of privacy regulation in the U.S. and abroad can create challenges in these deals. And there are some industries where data is heavily regulated, leading to more hurdles to implementing the new technologies. We saw this with cloud technologies, and slowly but surely, the industry has come to terms with how to address these risks, so we expect the same to happen with AI technologies as these technologies mature. In this area, we are working closely with our Privacy, Security & Data Innovations team to help clients understand and mitigate these risks. Other risks that need to be carefully considered include cybersecurity and intellectual property concerns. 

What excites you about working in this area?

The most exciting aspect about being a technology lawyer is that every couple of years there is new or evolving technology, so we have to continually be ahead of the curve and help our clients as they develop, procure and implement these technologies. Just as we were advising our clients on early transactions in cloud and SaaS a decade ago, we are now advising our clients on these new technologies. 

It’s inspiring work. Not only are we helping educate our clients as to the risks, but we’re helping early adopters of these new technologies through the contracting processes, particularly since current contract models may not fit these new technologies. That includes helping clients understand which stakeholders to bring to the table, since many of these subject matter experts exist outside of the IT department. Having those discussions and educating our clients is exciting to me – we bring all of our experience to bear and help everyone involved navigate the risks to reach their goals.