By Steve Novakovic, CAIA, CFA, Managing Director of Educational Programs, CAIA Association
Artificial intelligence may not yet be fully woven into our daily lives, but conversations about AI seem to be a regular occurrence. Particularly common topics include: Who will lose their jobs to AI, and how many? What must organizations do to avoid becoming obsolete? And how should companies and employees integrate AI into their work?
Only time will tell the true answers to these questions. What does seem certain is that the amount of disruption caused by AI will vary across industries and span a spectrum from minimal disruption (e.g., professional dog walkers) to maximum disruption (e.g., automating tasks such as data entry). Where exactly one’s job or industry falls on this spectrum may still be unknown, however, for many, it is clear which end of the spectrum they are likely to land on. For those in the professional training and teaching industry, the signs increasingly point towards major disruption.
Already, individuals are using AI tools to create self-guided learning programs. Want to learn a new language? One can just ask their favorite AI tool to create a curriculum outline, with clear goals, a structure to fit their lifestyle, and built-in review. AI can accommodate a variety of learning preferences, customizing the learning experience to support analytical, experiential, reflective, visual, and other learning preferences. As such, why would anyone pay hundreds or thousands of dollars for a single-delivery, one-size-fits-all learning experience from a professional training company?
In Q1, we saw several major headlines that spooked markets and foretold of doom and gloom across a variety of industries. Investment bank Jefferies introduced the term “SaaSpocalypse”, suggesting enterprise software companies are particularly vulnerable to AI. At the same time, research firm Citrini published a thought piece suggesting AI could be responsible for significant white-collar job losses. Should these, and other doom and gloom forecasts be right, what can we do to maintain relevance?
An AI “moat”
A concept applied in the world of business that is worth exploring in this discussion is one of competitive moats. A competitive moat is the idea that a business has a distinctive structural and durable advantage that allows the business to remain near the top of the industry and fend off competition. This concept has been around for centuries and gained substantial traction in the last 50+ years. While there are several types of moats, they can generally be categorized into a handful of sources:
Switching costs – the idea that it is costly (i.e., financial, time, etc.) to switch from an existing system. For example, a business may be fully integrated into the Microsoft ecosystem, switching to a different software solution could be time-consuming, and carry a high cost to port data and systems to the new provider.
Network effects – the idea that people want to be part of something because everyone else is. Someone uses WhatsApp because all of their friends and family use WhatsApp. If they don’t have WhatsApp they are literally left out of the conversation.
Cost advantage – the idea that the business is the lowest cost provider of a service in a way that can’t be replicated. For example, Saudi Aramco can extract oil at a cost lower than nearly any other oil producer.
Efficiency of scale – the idea that a company has reached a critical size that can’t be replicated by competition without a massive financial investment. For example, based on its sheer size and scale, Wal-Mart can provide services and price products in a way that other brick and mortar retailers simply cannot.
Intangible assets – this category covers several ideas, such as strength in brand (e.g., Louis Vuitton), intellectual property protection (e.g., patents on drugs), and regulatory licenses.
At a quick glance, it is easy to see some of these moats may help manage the disruption of AI, while others may not apply (or even favor AI as might be the case with cost advantage). There are two moats that stand out in particular for the professional learning industry in the case of fending off AI:
- Network effect – Is the learning experience so widespread it compels individuals to want to participate? One example might be fitness training. When all of someone’s friends go to the same gym, they may continue to pay monthly membership even though AI could create a customized fitness regime to help them more effectively achieve their personal goals at a lower cost.
- Intangible assets (specifically brand) – Brand can mean many things, but in this case, what brand offers relative to AI is trust and credibility. We still live in a world where AI is imperfect and can and does make mistakes. We can ask AI to teach us a concept, but there remains a risk that AI delivers incorrect information. Similarly, while AI can help teach professional skills, employers continue to place far greater trust in candidates who have earned recognized designations from credible training programs.
What may not be present in any of these moats, but may be a moat of the future, can be described as “the human touch.” Already, we are seeing signs of consumers eschewing AI solutions in favor of human-based experiences (e.g., a preference for a human as a customer service solution). There is a strong potential for this to play out in the training and teaching industry, with learners valuing human-based training solutions.
Automation versus Augmentation
In many ways, this conversation, and often the broader conversation around AI centers around the doom and gloom of automation, displacement, and obsolescence. And while that may be the ultimate fate for some professions, a more hopeful outcome is augmentation. An embrace of AI to enhance and improve services and outcomes, to transform the existing business or job to leverage AI for the benefit of the end user.
Whether a company has a competitive moat or not, if it isn’t already incorporating AI into their business, it is likely an eventuality. For those with moats, AI can help augment and strengthen what is already offered. For example, an AI tool trained on the proprietary curriculum and knowledge base (to ensure trust and credibility) can then design and deliver a customized learning experience to meet the preferences of the learner. In this example, the business retains the responsibility of managing the ‘body of knowledge’ and therefore provides the trust and curation that is not yet replicable by AI on a standalone basis.
Trust Still Needs Verification
Even as AI expands access to learning, the role of trusted institutions becomes more—not less—important. At the CAIA Association, we see AI as a tool that can enhance how professionals prepare for the designation, from personalized study approaches to more adaptive learning resources. But the core value of the CAIA Charter has never been the delivery of content alone. It lies in the standard it represents: a rigorous and practical curriculum, independent examination, and a globally recognized credential that signals both competence and commitment to the alternative investment profession. In a world where anyone can generate a learning plan with a prompt, the ability to demonstrate verified expertise becomes increasingly valuable.
Moving Forward
The clear path forward for any organization in the training and education industry is two-fold. First, identify the moat(s) that give the organization a distinct advantage over AI. In this exercise, don’t undersell the importance of “the human touch.”
Second, augment by instituting a mind-set of embracing AI. Continue to provide a service that AI just can’t offer (e.g., a network, trust, curation, humanness), while taking advantage of the benefits of AI (e.g., customized learning delivery). Don’t give learners a reason to venture out with AI on their own, instead support them in their learning journey by incorporating the AI tools they are using in other walks of their life.
This path certainly means disruptions, new tools, new processes, perhaps even new models, but does not mean obsolescence. Standing firm and fighting the AI revolution on the other hand, is likely a losing battle that risks a business ending in obsolescence.
The author did not use AI to write this piece; however, the author did use AI to help research for this piece.
About the Contributor
Steve Novakovic, CAIA, CFA is Managing Director of Educational Programming for CAIA Association. He joined CAIA in 2022 and has been a Charterholder since 2011. Prior to CAIA Association, Steve was a faculty member at Ithaca College, where he taught a variety of finance courses. Steve started his career at his alma mater, Cornell University, (B.S. 2004, MPS 2006) in the Office of University Investments. In his time there, he invested across a variety of asset classes for the $6 billion endowment, generating substantial insight into endowment management and fund investing across the investment landscape.
Learn more about CAIA Association and how to become part of a professional network that is shaping the future of investing, by visiting https://caia.org/