One of the greatest barriers to artificial intelligence (AI) adoption is trust. Amongst other things, this includes the defensibility of results, leadership’s support in both the sourcing and roll-out of AI solutions, and comprehensive roadmaps for continued professional development. All these examples seek to remove the mystery of AI. Mystery in this case refers to the opaque nature of how AI tools are rolled-out, and not a basic understanding of AI via its academic or practical definitions and general purpose. In the title of this post, I deliberately use the word ‘around’ instead of ‘about’.
When we do not fully understand what something is, we might need to learn about it. If we already understand what AI is, then our growth comes from studying around it by navigating its application specific to given roles across an industry or profession. I might understand what machine learning (ML) is in a general sense. I may be able to communicate the concept of ML and use that referred knowledge whenever the subject arises. But there is much more to be done if I hope to truly understand what its applications are as it relates to specific roles. Broadly approaching a topic like ML creates the risk of opening Pandora’s box.
The process of successfully adopting AI at scale is simply to involved to not have some form of industry certification. There is enormous value in the collaboration of industry professionals sharing ideas to navigate common problems. I have seen this every week on The Cowen Café; a weekly think-tank run by David Cowen of The Cowen Group. Like clockwork, 60+ leaders representing some of the largest law firms and corporations in America (and increasingly Europe) log-in to discuss challenging ideas and share experiences. The value this provides cannot be understated. Trying to navigate the implementation of technologies like AI without outside assistance is a herculean task. There is not enough time in the day to successful perform one’s job whilst simultaneously tackling the sourcing of an appropriate solution, growing internal support for that solution, and finally deploying the solution without aging at an unnecessary rate.
Steps to Developing Industry-Relevant AI Certification
Regardless of the topic, the same basic steps go into the development of a quality certification program. First, a complete due diligence process is required, defining the program’s objectives. This includes clearly understanding the target audience, the pain points the program is trying to fix, and ensuring there is a national-body plan on launching the engagement. These are just some of the considerations to be addressed in the due diligence process. This is also the time when thought leaders can define the need and ability to support a certification program. It is important to keep in mind that a certification program is not always the right response to a training need or pain.
After due diligence is complete and the organizing body has determined that AI certification is suitable for the legal industry, the following steps are required:
Certification is an ambitious goal, so it is important to consider several questions in the process of developing a suitable AI education program. This includes understanding whether the target audience has already achieved an advanced educational degree or employment-level training required to accomplish the requirements of their professional position. It also requires peer consensus on why the certification is ultimately necessary. Further, successful certification cannot be a flippant process to attract interest. It must be relevant and rigorous enough that it will lead to employment advancement or increased compensation. Avoiding the “nice to have” and creating an industry recognized “must-have” is critical.
To be successful, certification programs require the direct support of upper management. Developing an industry-focused AI certification program requires time, money, and a lot of patience. Even still, initial development times are dwarfed by editing and launching requirements, even before accounting for marketing. Without a robust marketing engine that includes incentive for certification, you are setting yourself up for failure. For AI to achieve its full potential, industry professionals need more to ensure a common language and access to reliable roadmaps for achieving their specific goals. This involves the development of recognized accreditation pathways like those provided by ACEDS and other professional bodies.