Successful Gen AI: Governance, infrastructure, and talent needs

Machine Learning


The reality is, Gen AI requires a robust, flexible infrastructure capable of handling massive amounts of data and complex calculations. Many organizations are finding their existing systems inadequate, with 71% of respondents agreeing that they need to modernize their infrastructure before moving forward with a Gen AI project.

Addressing the talent shortage

Perhaps the most pressing issue in the Gen AI space is the shortage of skilled professionals. In the survey, 61% of respondents believe most users don't know how to leverage Gen AI, and 51% reported a lack of employees with Gen AI expertise. This skills gap extends beyond technical knowledge; it also extends to a strategic understanding of how to plan and execute Gen AI projects, with 40% of respondents admitting they don't have enough knowledge in the field.

To truly harness the power of Gen AI, organizations need to focus on three key areas:

Robust IT GovernanceIt is important to develop comprehensive policies and guidelines for the use of Gen AI, including addressing data privacy concerns, ensuring regulatory compliance, and establishing an ethical framework for the development and deployment of AI.

Modernizing infrastructure: Investing in a scalable, flexible infrastructure that can keep up with the demands of Gen AI is essential, which may involve a combination of on-premise and cloud solutions, with 78% of organisations citing a hybrid approach as their preferred strategy.

Talent Development and Acquisition: Organizations should prioritize upskilling their existing employees and acquiring new talent with Gen AI expertise. This includes not only technical skills but also strategic competencies in managing and implementing AI projects.

The road to maturity for next-generation AI

As organizations navigate these challenges, their approaches to Gen AI will likely evolve. Currently, 96% of survey respondents prefer non-proprietary models, but in the long term, the use of proprietary models is expected to increase six-fold. This shift signals an increasingly sophisticated use of Gen AI as companies seek competitive differentiation through custom AI solutions.

“It's clear that enterprises are jumping on the Gen AI bandwagon, which is no surprise, but it's also clear that the foundations for Gen AI success have not yet been fully built fit for purpose and are yet to realize its full potential,” commented Ayman Abu El-Wafa, chief technology officer at Hitachi Vantara. “But to unlock the true power of Gen AI, we need a strong foundation with a robust and secure infrastructure that can keep up with the demands of this powerful technology.”



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