Three leadership lessons for winning with AI – IBM

Author

95% of AI pilots fail, according to an MIT report. It’s not because the technology doesn’t work, but because enterprises apply too narrow of a lens to their transformation. They’ve overlooked key components: processes, data, adjacent technologies and the people around them.

This point came into sharp focus at the HFS roundtable in September, where global leaders debated the role of AI in enterprise transformation. It became clear that technology isn’t the issue. The real issue is leadership.

Success with AI depends on leaders who can reimagine how their organizations work, redesigning processes, integrating data and empowering people to unlock AI’s full potential.

The leadership lessons behind AI success

Many companies have rushed to deploy AI, whether in customer service chatbots, marketing automation or HR self-service. But AI layered on top of broken processes doesn’t deliver the expected value. It ends up automating inefficiency, resulting in limited benefits.

The first leadership lesson is about process reinvention. Workflows must be reimagined end-to-end, not patched together. Leaders who take an AI-first approach, seek impact at scale and look beyond productivity gains can achieve sustainable value.

The second lesson is about data integration. Enterprise data is too often siloed and inconsistent. Without drowning in endless standardization programs, adopting a data mesh approach allows for connectivity and agility—both essential for AI to perform effectively.

Finally, the third lesson is about people, organization and culture. Success starts with a clear vision and empowered teams. Leaders must go beyond cost reduction and inspire a culture focused on creating value and driving meaningful change. Cross-functional collaboration and organizational agility are essential drivers of success.

Without these foundations, even the most advanced AI risks becoming another failed pilot.

Three leadership imperatives for Global Business Services (GBS)

As organizations scale AI across operations, they are entering a new era of digital labor—AI-driven automation embedded in core workflows.

This new workforce doesn’t manage itself. To harness it effectively, organizations and particularly their core functions (finance, HR, procurement and related departments), need to build new capabilities at the heart of their operating model.

If you envisage a future where 50% of your functional workforce is digital, then this shift becomes a real profession. It’s no longer an experiment or an “IT thing” for technology teams to handle.

We are entering a world of hybrid AI, where human talent and machine intelligence co-create value.

The same way enterprises accepted the hybrid cloud as the norm, we’re now seeing AI evolve into an open, hybrid ecosystem. ERP platforms, SaaS solutions and custom-built AI systems are all delivering new agentic capabilities and start colliding.

In this environment, success depends not just on deploying AI tools. It also relies on the ability to securely, ethically and reliably orchestrate workflows that combine humans and AI agents across multiple platforms and AIs.

While most organizations still focus on AI for productivity and automation, the next frontier lies in unlocking AI’s value in personalization and prediction.

• Personalization is emerging as a major differentiator in customer engagement, product recommendations and experience design.
• Prediction and performance insights remain largely untapped, yet they hold the key to top-line growth.

GBS can play a pivotal role by reimagining how process, data and AI intersect to deliver value in new, more proactive ways.

The leadership imperative for GBS

If these lessons hold true anywhere, it’s within GBS, where process, data and people intersect every day.

Enterprise functions, and particularly GBS leaders, have a key role to play in this transformation. Their new mandate is to be the trusted driver and execution leader of innovation, focused on business outcomes.

For decades, GBS has been viewed as a shared service provider, efficient, cost-focused and mostly back office. But today, business leaders are asking new questions: How are you helping us innovate? How are you driving growth?

This moment is an opportunity for GBS and GCCs to evolve from cost-focused service providers to orchestrators of enterprise-wide transformation and enablers of innovation.

Leadership in action: From six weeks to 60 seconds

These leadership lessons have come to life within IBM itself.

In early 2023, the CEO of IBM set the challenge to rethink and reshape IBM to “become the most productive company in the world.” A bold ambition and a target of USD 2.5 billion. Everyone rallied and collaborated in new ways to address this daunting challenge. Three years later, over USD 3.5 billion has been delivered.

Within marketing, we asked a simple but bold question: What if creating a marketing campaign can take sixty seconds instead of six weeks? Traditionally, producing a banner ad involved endless reviews, iterations and handoffs across marketing, design, legal and translation teams. The process required six weeks, a significant budget and untold patience.

By rethinking the process with an AI-first approach, we reduced that cycle to 60 seconds, not just faster, but also more effective. The ads achieved three times better outcomes than the ads created through the old, labor-intensive model. This transformation worked not because of AI alone, but because leadership reimagined process, aligned data and empowered teams—exactly the three ingredients that separate AI pilots from true enterprise transformation.

Looking ahead

There is a clear leadership opportunity for next-generation GBS—one that requires deep expertise of digital orchestration, governance, skills and business value creation.

• Digital orchestration: Integrate and coordinate multiple AI agents and workflows across platforms.
• Security and governance: Build frameworks and processes to ensure secure, compliant and transparent AI adoption and agent-to-agent orchestration.
• Skills transformation: Empower teams to train, optimize and govern AI systems—the lifeblood of future operations.
• Focus on business value: Drive measurable outcomes at scale, prioritizing speed and impact over perfection.

Because GBS sits across multiple functions, it can see beyond silos to capture value at scale. The future belongs to GBS organizations that inspire and treat AI as an enabler of smarter processes, deliver trusted governance and embrace bold, accountable leadership.

AI holds extraordinary transformative potential but only when organizations are ready to rearchitect their operations, embrace new skills and lead with purpose. The question is not whether you adopt AI, but whether you’re ready to lead the transformation it demands. Stay tuned for our upcoming white paper, co-authored with HFS. It captures the most powerful insights from our roundtable and offers a roadmap for GBS transformation in the age of AI.

Learn more about our Business Operations services

Hear about scaling AI and IBM’s own transformation journey from the HFS roundtable