For business operations, the traditional shared services model has been a cornerstone for efficiency, standardization, and cost-effectiveness. As the demands on these services grow and the pressure to deliver more [value] with fewer resources increases, the industry has embraced artificial intelligence (AI) as a transformative lever that can reshape how services are offered and encourage organizations to reexamine the traditional tiers and channels that have defined shared services and GBS models for years.
AI encompasses a broad range of technologies enabling machines to mimic human intelligence and react to human prompts or emotional cues. AI accesses and learns from data, identifying patterns, making decisions, and improving over time without explicit programming. Generative AI’s ability to develop new content in various formats, often indistinguishable from that of humans, has piqued the interest of shared services operators. Among the ever-increasing menu of available technologies, what is most important for shared services is the understanding that no single technology solves all problems. Therefore, it is important to resist the temptation to divert energy and resources from optimizing suites of solutions to a singular new technology, i.e., Generative AI (GenAI).
The technologies in our automation toolbox now, and those that are near commercialization, have the potential to save organizations time, effort, and money on an enormous scale. Our report dives into research around the current state of enterprise AI applications, where organizations are finding the most success, and what these organizations are considering as they build and integrate these technologies. Partner and Enterprise and Specialized Services Lead Brad DeMent and Partner, and Corporate and Shared Services Lead Jerred Crosby researched and wrote this report in collaboration with the Shared Services and Outsourcing Network. Click below to access the report.
