This is the second article of a 3-part series, "The Case to Embrace AI." This series examines AI usage among professional services firms, and more specifically, how some consulting firms, as focused as they may be on guiding clients on their AI journeys, could be overlooking important opportunities to put AI to work within their own companies. The series will outline some of the promising use cases for AI in a professional services firm, the benefits these use cases can provide, and the foundational elements firms need to put in place to reap those benefits.
Unlocking AI's Value Inside a Consulting Firm: Used the right way, AI is proving it can deliver ROI via new business models and business process improvements. Contributed by Carlos Sanchez
As is usually the case after a technological breakthrough's initial splash, wide-eyed curiosity has yielded to clear-eyed practicality as business leaders begin viewing AI technology through the more hardened lens of the return on investment it can potentially provide. These days, the question business leaders in pretty much every industry, consulting included, seem to be asking their preferred generative AI-driven digital assistant is, "What value can you add to my business?"
The short answer, it turns out, is: Plenty.
Citing findings from a 2023 IDC global survey of corporate IT buyers, Ritu Jyoti, the firm's group vice president of worldwide AI and automation research, reported that organizations recorded an average of 3.5X ROI for every dollar spent on AI. And they're spending big dollars on AI in search of those returns, according to Ritu, as organizations reported that their planned outlay on AI capabilities for the next 24 months has increased by an average of 23.4%. The professional services sector is expected to be among the most aggressive AI spenders, alongside banking, retail and manufacturing.
By 2025, according to IGT, the G2000 (the world's largest companies, essentially) collectively plan to allocate more than 40% of core IT spend to AI initiatives, "leading to [a] double-digit increase in rate of product and process innovations."
What kinds of innovations could consulting firms and professional services companies be pursuing with their investments in AI? Which business AI use cases show the potential to provide a firm — and its clients — with the greatest value? These are questions that firm leaders should be asking as they evaluate their IT spend and overall business strategy here in 2024 and beyond. Finding the answers requires a frank evaluation of the ROI business AI can deliver in internal use cases, and in terms of revenue-generation for commercial service and product offerings.
Business AI has been around a while, and there's a good chance you've employed it in using the machine learning-powered capabilities and intelligent automations embedded within the business software inside your firm's tech stack. These kinds of use cases typically are limited in their applicability and their value to a business. Now, however, firms are uncovering a huge range of possibilities for using business AI, and genAI in particular, in internal business process applications as well as customer-facing aspects of the organization.
Let's dig into some of the highly promising applications for genAI in terms of their potential value to a consulting firm.
- A catalyst for, and enabler of, new business models and revenue streams. Innovating on the product and service front with subscription-based and outcome-based services is one area where AI can really move the needle for a consulting firm. According to IDC, by the end of 2024, 33% of G2000 companies will exploit innovative business models to double the monetization potential of genAI. Instead of traditional fixed-price or per-hour pricing models, firms are exploring development of services built around their unique intellectual property or expertise, with genAI embedded as part of those offerings, then charging a set subscription fee for them, providing the client with cost certainty and the firm itself with a defined, sustainable revenue stream. A firm with supply chain management expertise could, for example, develop a service designed to curb revenue leakage in transportation/logistics, charging a fee that's scaled to the actual savings it delivers to the customer. Here genAI could work on two levels, providing the firm itself with insight on how to price and structure the service (essentially striking the right balance between risk for the firm and attractive pricing for the customer), while also working as the intelligent engine within the service, providing optimal transportation/logistics pathways based on a huge range of datasets.
- Intelligent, comprehensive workforce management. Managing internal and contingent/contractor resources, a persistent headache for many firms, becomes a more streamlined and intelligent process with genAI supporting in various areas. With a given set of parameters and the right prompts, it can perform skill-matching, evaluating skillsets, experience, availability, geography, projects pending and in the pipeline, and other factors, then recommend an optimal mix of in-house and contingent resources. It can recommend an optimal team makeup based on the parameters and priorities of an RFP. It can forecast resource needs and costs based on the project pipeline and prevailing market dynamics, and identify potential skill and resource shortages before they become problematic. When a project manager identifies a need for a resource with a very specific combination of skills, it can identify a person whose skillset exactly or approximately matches those skills (adjacent matching). And it can perform intelligent reverse matching for resource managers, recommending a well-suited project placement for a consultant who's on the bench. With the right prompts, parameters and data sets, genAI can do all this amazingly quickly and insightfully.
- Elevating client service. Say a client has an accounts payable issue. Instead of having to perform all the manual work that goes into reviewing information about the case and where it stands, then relying on less-than-complete information to make decisions about next steps toward a resolution, genAI can arm service teams with the analysis and information they need about a case, recommend next best options for resolution, then automatically generate communications to the client about the steps being taken. It can also flag more complicated cases that require deeper human involvement. The result: better overall experiences and outcomes for clients and client service teams alike.
In IGT's 2023 survey, 41% of IT decision-makers at professional services firms indicated they believed genAI and technologies like ChatGPT would disrupt their organization's competitive position or business operating model in the next 18 months. By exploring use cases like these, firms can begin to harness AI's disruptive powers to add value their business and their clients.
To read Part 1 of this series, click here.
Carlos Sanchez, Platinum Business Principal, SAP Carlos Sanchez has been a business and technical consultant for 25 years with multiple consulting organizations. He is currently a solution expert in the SAP Professional Services Global Industry Business Unit.
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