This article compares the different structural models of expert networks and determines the advantages of the traditional sourcing model, despite society moving toward artificial intelligence in many aspects. Can AI technology properly replace real people?
The digital age has enabled collaboration and information-sharing on a global scale, creating opportunities for people to exchange insights and gain valuable knowledge from industry experts. These opportunities are created through expert-matching services, also known as expert networks. They are emerging as a powerful tool to leverage the collective wisdom of experts in a variety of disciplines.
With the rise of expert networks, it is crucial to understand the different existing models to decide which network to choose. Two models exist today: the traditional model and the technology-driven model. The traditional model for expert networks is more like a concierge service, where human beings source experts based on industry and field, matching them with clients who require their services. These employees create a database and conduct thorough research to continually grow their list of potential experts. On the other hand, he technology-driven network is more like a search engine, an online database that displays all the qualified professionals within an industry and field.
There are also two revenue models for these expert networks; some of these services follow a subscription-based model that uses credits, and others use the pay-per-use model. Subscription-based revenue involves clients paying a yearly or monthly fee in exchange for credits they can use for consultations. They are typically one credit per one-hour discussion or up to two credits for "premium" experts. The pay-per-use revenue model means that clients are charged by the hour or minute of consultation time with their expert rather than having to stock up on credits. With this system, clients are only charged after receiving all the information needed. In also enables experts to charge what they deserve, down to the minute. This also allows the client to get the necessary information without paying for an hour of service if they only need a thirty-minute conversation. This system provides more flexibility in using expert networks, whether the client needs a one-time service or a continuous connection to skilled advisors.
The technology-driven model has several potential benefits, like a quick and efficient system and a well-maintained database. However, despite those benefits, there are considerable advantages to the traditional model that provide a greater degree of assurance to those looking to obtain expert insights.
The first advantage of the traditional model is that it allows clients to choose the expert they feel comfortable with, whereas using the technology-driven model means clients are at the mercy of the search engine to match with a qualified expert. The benefit of choosing experts is ensuring the clients’ comfort, unlike using the technology-driven model. With a model that relies heavily on AI, if clients do not feel comfortable with a particular professional, they must restart the process from the beginning. This can be frustrating for clients who want to save time searching for professionals. With the traditional model, the expert-matching service’s team efficiently researches and vets the experts so clients can prioritise conducting thorough and productive interviews with the professionals they are matched with.
Another advantage of a traditional model over a technology-driven model is that it carefully considers every individual need a client has. Technology-driven networks cannot catalogue every specific requirement a client may have and can only take minimal requests into account because of how they are programmed. The traditional model makes it possible to find advisors with the expertise needed because real people can adapt their research inputs based on tailored requirements and adjust their search to their clients’ demand.
The final advantage of the traditional model is that it offers a long-term relationship between the client and the expert. The experts are carefully selected to fulfil the clients’ needs, and these connections are more likely to be successful and long-lasting due to the diligent research conducted by the team working for the service.
There is one combination of all the possible models that puts clients’ and experts’ best feet forward. Imagine a traditional sourcing expert network that uses the pay-per-use revenue model. This combination ensures the best outcome for clients and experts who are a part of the network. Clients only pay for the consultation time they need when they need it and gain insights from the best advisors available, while experts share their in-depth knowledge with people who are genuinely interested in their insights and are paid for their expertise.
While both the traditional and technology-driven models are successful structures for expert-matching services and the world continues to trend toward AI technologies, it is essential to remember that there are still benefits to work produced by real people. The human-to-human interactive aspect of the traditional model allows for more accurate and tailored connections between clients and experts with reliably beneficial results.
