IBM’s Gurnani urges AI governance in tech training

AI governance should be an intrinsic part of tech skilling, according to IBM’s chief technology officer for the technology division, Geeta Gurnani, who stressed the need for a broader skill set as hybrid cloud and artificial intelligence become mainstream.

Hybrid cloud adoption varies across sectors

Gurnani noted that the pandemic accelerated the move to hybrid cloud, AI and related tools, but the level of maturity differs by industry. Banking, financial services and insurance, as well as telecom firms, are already ahead on the adoption curve, while manufacturing, retail and government agencies lag behind. “Most of the proof of concepts around hybrid cloud and AI were pilots and at the innovation phase, which is gradually getting mainstream recognition,” she said, highlighting a shift from experimentation to production.

She explained that many organizations have shifted workloads to the cloud over the past three years, yet the transition remains uneven. The main obstacle, she added, is not merely technology but the ability to integrate multiple cloud environments without creating blind spots that could expose data.

Key challenges: complexity, security and skill shortages

When asked why hybrid cloud adoption remains low in India, Gurnani pointed to three interrelated issues. First, the technical complexity of making disparate cloud platforms work together creates operational friction. Second, security concerns persist despite a range of techniques used to protect workloads. Third, and perhaps most pressing, is a talent gap that hampers effective implementation.

Compliance adds another layer of difficulty. Companies must meet regulatory requirements that differ across jurisdictions, and meeting those standards in a cloud context can be “very challenging,” according to the interview.

Talent shortage hinders progress.

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For businesses planning their next‑year strategy, she advised leaders to focus on resilience, performance, security, compliance and total cost of ownership. She warned against equating hybrid cloud with public cloud alone, emphasizing that each workload may demand a different approach.

AI governance emerges as an important skill

Beyond the broad technical competencies, Gurnani singled out AI governance as an important area for upcoming training programs. She defined it as a legal framework designed to ensure that machine‑learning systems are built and deployed in a way that serves humanity fairly. With a proliferation of models created in recent years, managing them and maintaining trust in AI outputs has become a major concern.

“Now that industries are adopting AI at scale, there will be a greater challenge around Trustworthy AI,” she said, urging that AI governance be woven into the fabric of technology education.

While many firms are already investing in skilling initiatives, the gap remains noticeable. A practical step, she suggested, is to embed governance principles into curricula for developers, data scientists and architects, so that compliance and ethical considerations are not an afterthought.

If companies can align their hybrid cloud strategies with strong AI oversight, they may avoid the pitfalls of fragmented security and compliance failures. However, the path will require coordinated effort from both leadership and the broader workforce.

Gurnani also addressed gender diversity in tech, noting that companies are increasingly embedding inclusion into their policies. She highlighted the role of department heads and senior leaders in driving initiatives that give women and marginalized groups the tools to advance in a traditionally male‑dominated field. Progressive policies, she said, can help level the playing field and support career growth.