Last week, I penned a blog series around the special White-Collar Crime section in the July Harvard Business Review (HBR). This week, I am writing a blog post series based upon the MIT Sloan Management Review Special Report: Making Good on the Promise of AI. Today, I want to consider the article People and Machines: Partners in Innovation by Senén Barro and Thomas H. Davenport. I am using the article as an introduction into some strategies they have developed for Artificial Intelligence (AI) development and implementation.
It would seem axiomatic to note that every company has a different risk profile, risk management strategy and risk-appetite. In the anti-corruption compliance world this means you must evaluate your own risks and then manage them through a variety of risk-management tactics and techniques. This maxim holds true with AI development and implementation as well. In the headlong rush to adopt AI, many companies do not stop to consider precisely why they need such tools and how they will best utilize them going forward.
More importantly, the thoughtful adoption of “intelligent technologies will be essential to survival for many companies. But simply implementing the newest technologies and automation tools won’t be enough. Success will depend on whether organizations use them to innovate in their operations and in their products and services — and whether they acquire and develop the human capital to do so.” The authors believe, “there is no simple recipe for successful innovation based on automation. Different companies will have different opportunities to put intelligent technologies to work.” I have adapted their strategies for the compliance professional.
It Still Starts at the Top
As it always seems to be in compliance, it all starts at the top of the organization. This holds true with AI development and implementation. This means that you should have training for the executives charged with making the strategy decisions about AI. This is because “If leaders underestimate the potential of these technologies, their companies will miss opportunities to benefit from them. On the other hand, if they overestimate it and initiate projects that are too ambitious and costly, they will waste resources and perhaps even generate a bias within the company against new projects, even those that are reasonable.” To prepare senior management to make future decisions, you might consider holding educational sessions for top executives on “what AI is, how best to manage it, and what it might mean for employees.”
Develop a Roadmap
As with any compliance project, implementing an AI initiative “requires having a road map that describes the objectives, the necessary resources, and the implementation schedule. A good road map should help the organization anticipate the potential benefits beyond the most obvious ones and should include a communication strategy, both internal and external, especially when intelligent automation projects might lead to a reduction in jobs.” Moreover, as this is a project that will most probably be closely watched you might want to bring a project management specialist to help shepherd it through development and on to implementation.
Focus on immediately valuable projects (and be wary of initiatives that are too ambitious)
As most Chief Compliance Officers (CCOs), compliance practitioners and compliance departments lack significant AI experience, you “should focus initially on low-hanging-fruit projects that will enable them to gain experience. Highly ambitious tend to take far longer than researchers expected.” By combining several manageable projects in a single business area or risk, you may well have a better chance of yielding the type of results which will keep you in good stead, rather than trying to pursue one big one. The authors state, “The objective should be clear; even in cases where the goal is automating tasks previously performed by workers, key workflows should be designed or redesigned, focusing on the division of labor between humans and smart machines. The aim throughout should be innovative and effective work design, not just cost reduction.”
Invest in Your Team
Now that the Department of Justice (DOJ) has reaffirmed its consideration of the funding provided to the corporate compliance function, as well as an emphasis on the training and capabilities of your compliance team, as laid out in the DOJ Evaluation of Corporate Compliance Programs, 2019 Guidance, you should use this to invest in your compliance team regarding AI, both in development and capabilities.
The same is true for those compliance team members who will be working with your AI tool. Here, you should consider having personnel on your compliance team as part of the AI development time, serving as subject-matter experts (SMEs). In addition to their input into the overall design process, it would allow them to be “lead users of early versions of AI systems and provide feedback on what works” and what does not. Here the authors cause, “you should plan to develop or hire your own people as opposed to only borrowing them from consulting firms or vendors.” This is because you will need to provide a deep understanding of the business and current and evolving compliance user requirements, which are things that experienced compliance team members inside the company can best provide.
Making Improvements
The AI tool you immediately bring to bear should be suited for the projects at hand. However, as AI technologies are improving quickly, innovation based on automation needs to be continuous rather than episodic. This ties directly to another key component of the 2019 Guidance, which mandates continuous improvement in a corporate compliance regime. The authors point to “recent advances in natural language generation enable organizations to incorporate narrated reports into their business intelligence applications. This new capability may greatly increase the ability of nonexperts to understand technical and financial reports.”
The Bottom Line
Compliance professionals need to recognize that AI will find its way into more and more functions in the coming years. Compliance solutions powered by AI will reduce costs and improve productivity. The authors end with the following, “However, we expect that the greatest impact will be to drive innovation deeper into the business — and for that to happen, people and machines must be partners in the innovation process. Investing in intelligent technologies and in human resources capable of using them, cooperating with them, and innovating from them may be costly. But failure to do so will be much more costly.” The bottom line is that CCOs, compliance practitioners and the compliance profession need to embrace adaptive learning technologies such as AI or they will be consigned to the dustbin of no longer relevant corporate functions.
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