Introduced by EdgeVerve
Earlier than addressing International Enterprise Providers (GBS), let’s take a step again. Can agentic AI, the kind of AI in a position to take goal-driven motion, remodel not simply GBS however any type of enterprise? And has it achieved so but?
As with many new applied sciences, rhetoric has outpaced deployment on this case. Whereas 2025 was “imagined to be the 12 months of agentic AI,” it didn’t prove that manner, in line with VentureBeat Contributing Editor Taryn Plumb. Leaning on enter from Google Cloud and built-in improvement atmosphere (IDE) firm Replit, Plumb reported in a December 2025 VentureBeat put up that what has been lacking are the basics required to scale.
Given the expertise of Giant Language Mannequin (LLM)-based generative (gen)AI, this final result isn’t a surprise. In a survey performed on the February 2025 Shared Providers & Outsourcing Community (SSON) summit, 65% of GBS organizations responded that that they had but to finish a GenAI challenge. One can safely say that the adoption of the extra not too long ago arrived agentic AI continues to be in its very nascent levels for enterprises, together with GBS.
The function of agentic AI in International Enterprise Providers
There are good causes, nonetheless, to concentrate on the super potential of agentic AI and its utility to the GBS sector.
Stripped of hype, Agentic AI unlocks capabilities within the orchestration layer of software program workflows that weren’t sensible earlier than. It does so by a variety of methods, together with (however not requiring) LLMs. Whereas enterprises might certainly be lacking sure fundamentals wanted to deploy agentic AI at scale, these stipulations are usually not out of attain.
As for GBS and International Functionality Facilities (GCCs), they’ve already been present process a makeover, from back-office extensions into more and more strategic enterprise companions. Agentic AI is a pure match as a result of considered one of its normal use instances includes IT operations or customer-service brokers, performance already throughout the present GBS and GCC wheelhouse.
So sure, agentic AI might probably remodel the GBS sector. Trade leaders can greatest transfer towards scaled deployment by taking a methodical strategy.
5 steps for deploying agentic AI in GBS
Agentic AI just isn’t the one sport on the town. As famous, there’s GenAI, used primarily for content material creation. However broadening the scope, we are able to additionally level to predictive AI and doc AI, used respectively for forecasting and information extraction. (Neither requires LLMs.) Publicity to preexisting AI bodes properly for the way forward for agentic AI.
First, these flavors of AI are mutually supportive, stacked (somewhat than siloed) in trendy programs. Agentic AI, particularly, is positioned to attract upon the others. Second, having lived by the hype cycle of GenAI, trade leaders could also be inclined to take a extra measured – and productive – strategy to agentic AI.
Quite than speeding right into a pilot, the trade would do properly to prep fastidiously (steps 1-3). When mixed with the appropriate take a look at challenge (step 4), these actions can pave the way in which for a scaled-up deployment of agentic AI (step 5):
Know thy processes. Enterprise operations might be sophisticated. Contemplate a prime international transport and logistics agency, whose hundreds of full-time workers at its seven GBS facilities supported greater than 80 processes involving extremely advanced, manually intensive workflows with large regional variations. Solely by first understanding present processes and workflows does a corporation like this stand an opportunity of with the ability to rethink or rework them.
Know thy information. Carefully associated are the info that workflows rely on. How do these information stream from finish to finish? What do the pipelines appear like? The place are the important thing APIs? Are the info structured or unstructured? Do the sources embody information platforms (programs of report) and vector databases (context engines), each of which AI brokers have to make good choices? What sort of information governance and safety prevail? How would possibly these change in an agentic AI state of affairs?
Establish the issue. Within the case of the transport agency talked about above, the complexity and variation of the workflows, in addition to their handbook depth, uncovered it to vital prices, lapses in service degree agreements (SLAs), poor buyer expertise and heightened compliance and authorized dangers. As soon as named, an issue logically turns into a possible use case with discrete aims.
Pilot an working mannequin. Choices embody consolidating efforts in a Middle of Excellence (COE), democratizing improvement by citizen-led approaches, and partnering by Construct-Function-Rework-Rework-Switch (BOTT) fashions, amongst others. With out structural readability, even promising AI pilots are troublesome to increase past their preliminary area. The mannequin also needs to replicate actuality. Probably involving a number of, parallel brokers in pursuit of coordinated targets, Agentic AI continues to be constrained by atmosphere, complexity, dangers and governance.
Scale up. Profitable pilots result in their very own subsequent steps. Take the fragmented expertise of a giant multinational financial institution in Australia. After automating a number of non-core processes by Automation COE, the financial institution realized it wanted to investigate and enhance its most advanced workflows. It chosen an over-the-top software program platform that enabled it to finish greater than 100 discovery initiatives in beneath 14 months. Pilots thus might develop, changing into enterprise-wide initiatives.
What agentic AI seems to be like at enterprise scale
Solely scale can yield actual influence. The transport supplier, with its seven GBS facilities, ended up with expertise able to constructing information pipelines, digitizing advanced paperwork, making use of rule-based reasoning throughout country-specific exceptions and orchestrating work throughout groups. That basis led to an AI-first transformation of about 16 initiatives, exponential progress in automation and vital effectivity features.
By unleashing capabilities on the orchestration layer – enabling contextual notion, cross-domain collaboration, and autonomous motion aligned with governance – agentic AI can turbo-charge operations, each AI and human.
Contemplate a procurement course of. Whereas doc AI can extract information from buy orders, obviating sure handbook checks, an AI agent might additionally consider vendor danger, cross-reference compliance requirements, confirm finances availability and even provoke negotiation whereas maintaining audit logs for regulatory reporting. In a monetary advisory state of affairs, whereas predictive AI can analyze tendencies, an AI agent might take additional motion, aiding professionals particularly enterprise items on focused strategic investments.
Observe that the agent isn’t changing human judgment, however extending it, making certain choices are made sooner, extra persistently and on a scale.
From standalone automation to agentic ecosystems in GBS
GBS is uniquely positioned to guide the enterprise into the agentic AI period. By design, GBS sits on the intersection of processes and information throughout a number of enterprise items. Finance, HR, provide chain and IT all stream by the shared companies mannequin. This central vantage level makes GBS an excellent launchpad for creating agentic AI ecosystems.
An ecosystem differs from standalone automation. Brokers don’t carry out duties in isolation. Quite, they work as a part of an interconnected system. They share insights, be taught from each other and coordinate to optimize outcomes on the enterprise degree. Deployed inside a GBS or GCC, Agentic AI can speed up their ongoing transformation, enabling them to leapfrog incremental automation and function on the degree of end-to-end course of orchestration.
N. Shashidar is SVP & International Head, Product Administration at EdgeVerve.
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