Quick Overview

  • According to a report released by Pluralsight on ThursdayReport, talent gaps and technical barriers are hindering the strategic adoption of generative AI capabilities. The IT workforce training company surveyed 600 technology decision-makers.
  • Although two-thirds of respondents said their organizations have short-term AI plans in place, only one-third have a long-term adoption strategy. More than half of respondents noted a lack of fully mature data systems to meet AI's technical and operational demands.
  • "There is a serious gap between organizational ambition and actual readiness when it comes to AI adoption," said Chris McClellen, Chief Product and Technology Officer at Pluralsight, in Thursday's announcement. "While many companies recognize the importance of AI, the lack of long-term strategy, mature systems, and comprehensive workforce upskilling to support AI needs prevents them from fully leveraging AI's potential."

Deep Insights

Generative AI has tested the mettle of enterprise data systems and technical skills, exposing weaknesses in both across industries. CIOs are responding by increasinginvestments in AI talent recruitment and upskilling programs, while spending on data hardware andinfrastructure has also surged。

According to Pluralsight, efforts to lay the groundwork for AI adoption have yielded mixed results so far. Two-thirds of respondents said more than half of their employees have good AI skills, but three-quarters reported pausing or delaying AI projects due to a lack of sufficient talent.

Two years after ChatGPT's debut, many enterprises are eagerly awaiting signs of return on investment from generative AI. According to a survey released by Accenture on ThursdaySurvey, as of last year, more than one-third of enterprises have successfully scaled generative AI use cases. The survey covered 3,450 C-level executives. However, only 13% said the technology has created significant value.

Although many organizations have yet to overcome challenges in data readiness, process restructuring, and executive support, the professional services firm found that the banking and insurance industries have succeeded in scaling domain-specific AI applications with measurable ROI.

Successfully deploying AI assistants, chatbots, and next-generation agentic tools requires targeted, sustained investment in workforce and technology modernization.

Manulife Financial, in Thursday'sannouncement, said that after a decade of actively investing in AI capabilities, it has rolled out its proprietary generative AI assistant, named ChatMFC, across its global workforce.

The company has invested billions of dollars to build its digital capabilities through investments in cloud-based data and AI platforms, AI skills development programs, and a team of 200 data scientists and machine learning engineers.

"We have doubled AI-driven business impact by diversifying and expanding solutions, strengthening data and AI platforms, and practicing responsible AI governance," said Jodie Wallis, Global Chief Analytics Officer at Manulife, in the announcement.

The company said it expects its AI investments to deliver a threefold return within five years.

For many companies, sustaining technology spending remains a major hurdle. More than half of respondents in the Pluralsight survey said their organizations invest less than $500,000 in AI initiatives.

Nagendra Bandaru, Managing Director and Global Head of Wipro's Enterprise Futuring business, said the scale and scope of investments make the prospect of ROI unclear. Bandaru told CIO Dive that IT executives face a "three-headed monster" on the path to AI adoption—legacy system complexity, broken processes, and vast amounts of unclean data.

"All three must be addressed simultaneously for AI to run seamlessly and deliver ROI," he said.