Obstructing revenue for consultants and in the learning and development industries: Is artificial intelligence a real and operative threat?

AI's integration into the learning and development sector is reshaping traditional consulting models with both opportunities and challenges. While AI creates new revenue streams through enhanced service value and operational efficiency, it also introduces competitive pressures and may reduce demand for custom human consultancy. Here are three ways AI could boost revenue streams for consultants, and three ways it might decrease them.

First, AI enables highly personalised learning experiences. Using adaptive learning algorithms and data analytics, consultants can create programmes that adjust to each learner's needs. This improved engagement and better outcomes justify premium pricing, as clients value customised, results-driven programmes.

Second, AI-driven automation streamlines operations. By automating routine tasks—content updates, progress monitoring, and aspects of curriculum design—consultants can serve more clients with fewer resources, cutting overhead costs and increasing profits.

Third, AI-powered analytics reveal deeper insights into learner behaviour and programme effectiveness. These insights help quantify training programmes' return on investment (ROI) more clearly. With concrete data demonstrating value, consultants can establish themselves as strategic partners, securing long-term contracts and commanding higher fees.

However, AI's growing accessibility may saturate the market and commoditise learning solutions. As sophisticated AI tools become available to in-house teams and smaller providers, clients may choose cost-effective automated solutions over external consultants. This democratisation of AI capabilities threatens the premium pricing of traditional consulting.

Moreover, growing AI capabilities may reduce the need for human expertise in areas where consultants traditionally excel. As clients embrace fully automated platforms for training and analytics, demand for specialised human consultancy could decline, leading to lower fees and fewer high-margin projects. Furthermore, the automation of tasks (e.g., policy development, evaluation, testing and documentation) will become increasingly widespread, replacing entire departments and, thereby, cutting off a key revenue generator for consultants.

Finally, AI-powered learning management systems enable direct client access. Organisations can bypass consulting firms by using platforms that offer AI-driven personalised learning, content delivery, and performance tracking. This shift may pressure consulting fees downward as the market embraces technology-driven solutions. The same can be said of learning and education as students can create their own courses merely by prompting a generative AI model.

In summary, while AI offers powerful benefits—personalised learning, operational efficiency, and advanced analytics—that can increase consultant revenue, it also brings risks through increased competition, reduced demand for human expertise, and service commoditisation. Success will depend on how consultants adapt their value proposition in this increasingly automated landscape.