Transformative, but slower adoption ahead for Gen AI

While Gartner is anticipating a rapid shift toward mainstream adoption for Generative AI within procurement over the next two years, a recent report from Deloitte suggest it is not here yet across the broader supply chain ecosystem.

Deloitte’s report, “Gen AI transforming transportation: Lessons from the frontier of an emerging technology,” found that while nearly all transportation executives (99%) expect the technology to transform their industry, only one in five surveyed companies have matured their GenAI efforts to broad implementation. Additionally, 71% of the 200-plus executives surveyed expect the transformation to take more than three years, which Deloitte noted is slower than most other industries.

Within transportation, asset management, route optimization and warehouse operations are seeing the highest adoption rate so far, but most implementations are limited to date. However, those companies are reporting “extremely high” or “high economic” value in their use cases.

The survey, completed in July of this year, found that companies looking at more qualitative goals reported higher success rates. Conversely, companies looking for “financial-oriented benefits” such as improved efficiency and reduced costs are lagging behind.

Among survey respondents, the most common use cases for Gen AI are to improve traceability (75%), enable dynamic supply chain decisions (74%) and enhanced inventory efficiency (67%). Risk management (39%) and governance (33%) are among the largest barriers to Gen AI adoption in transportation.

Of the biggest concern, though, is data, with 40% citing misuse of data as the biggest Gen AI-associated risk.

“While it can still be considered early days in gen AI adoption, this technology has the potential to move quickly from novelty to necessity. Leaders will increasingly expect return on their Gen AI investments. Understanding where success is emerging and which challenges appear most frequently, and learning how the savviest are navigating, can help chart a course to effective adoption, and to the leading edge of the coming industry transformation,” Deloitte wrote in its report.

Within supply chain as a whole, 18% of respondents said they have at least broad implementation of Gen AI, while 57% more said there is at least one limited implementation ongoing. Another 16% have a pilot project in the works.

The survey results are not that dissimilar from other surveys. While there is intense interest in implementing Gen AI, and widespread agreement on its potential impact, many companies are moving slowly with projects.

IT excited, others not as much

Another survey from Gartner around the same time found that while IT departments are excited about Gen AI, business-led roles are less enthusiastic about it, with only 12% of business-focused roles indicating GenAI was the top priority, compared to 28% of IT roles. The data may indicate that GenAI use cases are currently perceived as less tangible and directly tied to core supply chain processes, Gartner noted.

Specifically, prioritization of AI (including machine learning) in general lagged in Western European companies, with just 14% of respondents citing it as a top priority. Conversely, 26% of North American leaders said it was.

“While enthusiasm for both traditional AI and GenAI remain high on an absolute level within supply chain, the prioritization varies greatly between different roles, geographies and industries” said Michael Dominy, VP analyst in Gartner’s Supply Chain practice. “European respondents were more likely to prioritize technologies that align with Industry 4.0 objectives, such as smart manufacturing. In addition to region differences, certain industries prioritize specific use cases, such as robotics or machine learning, which are currently viewed as more pragmatic investments than GenAI.”

Gartner noted that regions where manufacturing was a larger portion of the business environment tended to favor robots over AI or Gen AI. For instance, 14% of western European companies noted robots in manufacturing as their top priority while just 1% of their North American counterparts said robots was a top priority.

“The variation in regional priorities has implications for those devising supply chain technology roadmaps,” said Dominy. “Companies that have supply chains and operations in multiple geographies might find it more beneficial to invest in digital technologies differently by region versus more common approaches which tend to be by function.”

Gen AI use cases expand

With that said, use cases continue to grow.

The past year has seen the number of Gen AI use cases expand, with additional capabilities being added by vendors across the sourcing and procurement landscape, Gartner noted. These include contract management, sourcing and supplier management with additional expected use cases to include supporting supplier performance management, P2P and analytics.

“The window for building competitive advantage through early adoption of Gen AI in procurement is narrowing,” said Kaitlynn Sommers, senior director analyst with Gartner’s Supply Chain Practice. “Despite this, procurement technology leaders should remain aware of the obstacles to successful implementations, notably in the areas of data quality and integration of GenAI with their current systems.”

Sommers added that companies should look to launch “targeted use-case pilots” that can help clarify what capabilities are scalable. Also, monitor developments in the market and look for opportunities to leverage Gen AI without the need to build proprietary infrastructure.

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