Global business services: The true generative AI leader
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Global business services: The true generative AI leader

How GBS can become a strategic consulting partner by scaling generative AI across the enterprise

Global business services (GBS) organizations are at the heart of large enterprises. Traditionally focused on process improvement and cost control, GBS teams bring together different functions — including finance, procurement, HR, IT, and more — to centralize and standardize how they work.

But today's expectations are higher. Much higher.

To stay competitive, enterprises are asking GBS leaders to support business innovation, enable end-to-end process integration, improve experiences, and promote the adoption of new technologies like generative AI (gen AI).

This is why leading GBS organizations are pursuing a digital-first strategy. And the most forward-looking GBS leaders are already using gen AI to support their work.

For example, they're using automation and generative AI to create a better accounts payable help desk experience. Help desks now respond to supplier payment queries 35% more efficiently by querying the ERP for payment information and structuring messages for agents. And this improvement is expected to continue.

The opportunities for GBS organizations can, however, go even further.

Taking the lead on how their companies adopt gen AI – from identifying the right opportunities to embedding the tech – will demonstrate how GBS organizations can evolve from a process-focused support system into a strategic consulting partner.

And for good reason; they're naturally suited for it.

Why GBS is poised to lead on gen AI

GBS organizations are at the core of the corporate structure, giving them a unique view across the business and the ability to drive success with gen AI.

“We're at the heart of the company and experts in orchestrating capabilities. With our deep understanding of every facet of the business, we are the best place to start."
Mariano Andrade GBS leader of Johnson Matthey, a global leader in sustainable technologies

Additional strengths that GBS teams bring to adopting generative AI company-wide include:

  • Technology expertise: They're already skilled in driving change with tech, including prescriptive and predictive analytics, AI, and intelligent automation to, for example, anticipate late payments and realize touchless invoicing
  • Access to data: They have the data essential for training and fine-tuning gen AI models to make them more accurate, effective, and tailored to a business' specific needs
  • Knowledge of best practices for tech rollouts: By focusing on comprehensive planning, stakeholder engagement, rigorous testing, and training, GBS teams understand how to deliver standardization and smooth implementation with technology
  • Cross-functional integration: Naturally, at the cross section of different business functions, GBS teams have a full understanding of the organization, which is essential to integrating new technology in line with company goals. For example, leading elevator manufacturer KONE connected its record-to-report, sales-to-cash, and source-to-pay processes end to end across the business, aligning its F&A operations with new business leadership. As a result, 40% of full-time employees are now focused on customer-oriented tasks, and it has improved the employee and supplier experience

But while GBS are positioned to generate significant impact, they'll also need to overcome specific gen AI challenges – some of which they've inadvertently placed on themselves.

Moving beyond productivity – and past mistakes

Many enterprises have experienced the reality of technology not meeting its initial promise. In the case of robotic process automation (RPA), for instance, many companies took a piecemeal approach, which resulted in glimmers of innovation at the microlevel but no significant improvements to scale across the organization. Businesses must learn from these mistakes by enabling GBS teams to look at gen AI more holistically and deliver on enterprise-wide goals.

But to do this, GBS must evolve from a transaction-focused support system to an outcome-driven consulting arm.

Only this mindset shift is yet to extend behind the very highest-performing GBS organizations.

SSON's World's Best GBS list shows that GBS organizations continue to place high value on productivity, citing it as one of the main key performance indicators (KPIs) used to measure GBS performance. Not only that, but multiple award recipients also listed productivity as part of their value propositions. And recent research by analyst firm HFS, with over 600 business services decision-makers across Global 2000 firms, reveals that nearly 50% of GBS units are focused on cost savings.

However, even after they've made the mindset shift, leading GBS organizations are actively addressing additional challenges to adopting gen AI across the enterprise. These include:

  • A fragmented ERP and technology landscape: Businesses need advanced digital tools to bridge the gaps
  • Lack of resources: Since current GBS teams mainly focus on transactional tasks, they may need upskilling to fully understand gen AI's capabilities and adopt them successfully. And employees across the business may need similar training to work well with AI-enhanced processes
  • Disconnected processes: Siloed processes can prevent generative AI from accessing the large amounts of data it needs to learn
  • Insufficient architecture: To harness its true potential, GBS organizations need a robust platform to integrate generative AI with the company's existing tools. This can, however, create a heavy dependency on product vendors to set up, run, and fix these systems, potentially leading to vendor lock-in or other operational risks, like unexpected downtime or service issues
Insight hero talking technology services

Once GBS teams overcome these hurdles, they'll be able to capitalize on the tremendous opportunity that generative AI offers, such as boosting revenues, improving customer and employee relations, and finding new sources of competitive advantage.

But the next question is: what steps should GBS organizations take to transition into a strategic partner that leads enterprise-wide technology adoption?

How to carve out a new role for GBS as gen AI transformation partner

Based on our experience working with Fortune 500 companies across the globe, we have some advice to share on how GBS teams create the most value for their business from generative AI:

  1. Take the lead on business disruption. Get top leadership up to speed on generative AI opportunities so you can quickly become a more strategic partner to the wider enterprise. Work together to build a gen AI ecosystem, which will include solution providers to pilot gen AI offerings
  2. Build a hybrid task force within GBS. Because gen AI will need continuous monitoring, as well as more research to fully understand the opportunity, establish a center of excellence with service and tech partners to complement your talent pool
  3. Bring in the right skill sets. Adopt a two-fold strategy that balances upskilling and hiring talent like data scientists and AI experts. Consider having industry experts train a limited number of talent with AI, machine learning, and natural language processing knowledge. Then have these trained employees pass their new knowledge and skills to their colleagues
  4. Integrate gen AI into the tech stack. Embed generative AI into existing workflows to make them more seamless and connected. Then monitor the outcome on a regular basis and adjust as needed
  5. Build a robust data foundation. Focus on high-quality data acquisition systems and consistent data quality practices to make sure generative AI can process and analyze data to drive valuable insights
  6. Establish governance. Create a responsible gen AI framework that takes all stakeholders into account and prioritizes transparency, accountability, data privacy, and eliminates bias
  7. Build a service partner support system. Explore existing ecosystems and service offerings to bring forward different perspectives and experiences to support the successful adoption of gen AI
  8. Experiment continuously. Tap into the shared knowledge and ideas of everyone in the enterprise so GBS can explore new possibilities and learn from mistakes. This will guide the enterprise toward which initiatives to prioritize and deliver better ROI

The impact of elevating GBS from productivity support system to strategic consultant

GBS leaders who quickly embrace generative AI and take on a new outcomes-focused role can expect to make improvements in several areas:

Improved employee productivity with hyper-efficient automation and data analytics

Thanks to real-time translation and language processing, GBS teams can expect increased agent speed for all, especially for those not working in their first language. And because gen AI can gather and understand information from various places, it reduces the need to pass a task, information, or a request between teams multiple times. This creates more efficient workflows with more integrated and standardized data.

Improved performance

Generative AI significantly enhances finance performance by reducing costs and driving efficiencies. For example, it streamlines operations, making better use of working capital. And it can perform tasks remotely or automate processes that once required physical oversight.

In addition, it offers an adaptable approach that can manage on-the-fly situations with ease.

“Gen AI gives you that flexibility to be more human, reducing rigid structures while still delivering consistent outcomes."
Mariano Andrade GBS leader of Johnson Matthey

Most importantly, gen AI delivers crucial analysis and insights, helping leaders make better decisions and mitigating revenue leakages. But there's more to generative AI than productivity…

A competitive advantage with superior customer experiences

Generative AI improves the end-customer experience, creating faster and more customized responses, which lead to higher satisfaction and improved customer loyalty.

For instance, a multinational technology company uses gen AI not only to craft personalized replies but also to serve as a virtual subject matter expert that can address agent inquiries, which enhances the quality and reliability of customer service interactions. Gen AI can also reduce the time it takes to reach the right customers with advanced targeting and personalized marketing.

Enhanced business continuity and sustainability

Implementing generative AI enterprise-wide enhances business continuity by driving smarter decision-making across all departments. It also optimizes the supply chain, reducing disruption risks and improving inventory management.

For example, a global telecommunications holding company uses generative AI to empower its purchasing officers to correctly identify order stages, recommend actions, and improve the accuracy of their risk classification. The business can now better mitigate potential supply chain disruption with a more proactive and informed procurement process.

Consequently, with generative AI's continuous process improvement and standardization, organizations will benefit from consistent, reliable outcomes that nurture stakeholder trust. This trust is crucial for maintaining business continuity and achieving lasting growth in today's fast-paced business environment.

The road ahead

By leading the adoption of generative AI across the business – and with a shift in mindsets – GBS teams can go beyond simply cutting the cost of back-office functions. They'll demonstrate their role as a consulting partner that redefines a company's digital landscape, customer and employee experiences, and competitive advantage.

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