Supply Chain Matters provides a perspective of Generative AI’s timeline on supply chain business processes and the importance of continuing business systems support during that transitionary period.

 

The Quest for Generative AI Skills

This week a published report from The Wall Street Journal titled: Tech Job Seekers Without AI Skills Face A new Reality (Paid subscription), captured our Supply Chain Matters attention.

The essence and takeaways from this published report is that the promise and interest levels surrounding applications leveraging Generative AI technologies has now provided a discernable impact on the existing IT job market.

The opening paragraph tells it all: “The rise of artificial intelligence is affecting job seekers in tech who, accustomed to high paychecks and robust demand for their skills, are facing a new reality: Learn AI and don’t expect the same pay packages you were getting a few years ago.”

The statement, to state the obvious, has to be sobering for existing IT professionals, and that is going to likely include those directly supporting supply chain management business process and decision making needs.

Historic Context

The report observes that companies with capital and budget resources, most likely in the immediate pre-Covid timeframe, over hired in IT. They did so in order to be able to leverage market opportunities either brought forward with the pandemic, or be positioned for post-pandemic demand for Cloud based applications and infrastructure support software. We would add the observation that such staffing augmentation included business and supply chain technology providers along with large businesses with complex supply chain management needs.

The report’s cited statistics point to a forecast that the IT market in the U.S. will decline by 20,000 to 30,000 positions this year. Once more, the head of economic research for the online recruiting site Indeed, indicated that: “postings for coding jobs have fallen by 67 percent from March 2022 to the end of February.”

Now, with companies generally going back to cost-cutting in order to offset high inflation and perhaps decreased product demand levels, layoffs of IT workers have continued.

There is further the reality that those IT workers seeking new opportunities are discovering that existing skills, that warranted an attractive salary level, are no longer part of the demand and supply dynamic.

Instead, companies are reportedly of the view that increased automation, including that enabled by Generative AI technologies implies that entry level, systems or data management support “aren’t coming back.”

IT job demand is reportedly more focused on candidates with Gen AI and large language model skills, which are garnering the highest salaries.

Moment of Reflection

For this Editor and industry analyst, the report’s observation provided a moment of chuckle.

In my prior career, I worked at the then Sun Microsystems as a staff member in their internal IT development and support organization. For readers that might not be totally familiar with Sun, among the company’s many technology developments was the creation of the Java programming language which ultimately went on to revolutionize web and Cloud based systems development.

My moment of reflection was in attending a global wide all hands meeting at corporate headquarters to set strategic direction for the coming year. The excitement within hallway discussions and sessions was the potential of Java, and how Sun was going to be in the front of pack in developing new internal systems that would be both leveraging the technology internally, including supply chain support areas. At the same time, we would be demonstrating to the world the actual compelling benefits of technology.

Now for the moment of chuckle. I was asked to attend a working session that had to do with the planning of skills for supporting the company’s IT development needs in the coming year. Our chairperson confidently declared that we will be recruiting the best Java coders in the market, those with at least a minimum of one year of proven experience. That was bold, but, at the time, Java was only six months old in development at that time, and mostly centered on Sun’s internal R&D organization.

The obvious question to our presenter was how we will find these people given the math. The response was something to the effect, be creative- search far and wide, and if need be, we will train them.

Implications to Supply Chain Management

I have garnered quite a lot of experience and observation in high tech industry environments.

Readers who have heard me speak might recall my observations related to supply chain advanced technology cycles, namely that I have seen this movie many times before, and with the different endings.

Generative AI is no exception.

Yes, both technology providers and business level C-Suite executives are keen to understand, evaluate, and assess the value propositions of this technology. No company wants to find itself at a disadvantage from disruptive technology.

But, as our research advisories have indicated, it will take additional time for this technology to be deployed across mission critical business processes which include various aspects of supply chain management.

Foundational Preparation

There remains for many businesses foundational preparation needs, specifically addressing data management and harmonization needs. The reality remains that business are still drowning in data or collecting the wrong data. What is lacking are insights and predictive capabilities predicated on data.

Another reality is that visibility across multiple tiers of supply networks is still a work in progress. Some might argue there is little progress. Addressing such challenges are a foundational step toward successful leveraging of more advanced cognitive or generative AI capabilities.

Business environments remain highly dynamic and supply chain management teams across multiple industry settings are hard at work addressing challenges related to supply network resiliency, changing market dynamics and ongoing disruptive supply, transportation or logistics events.

Reader Takeaways  

The takeaway for supply leaders is to ensure a close collaboration with the organization CIO or senior support lead remains. It especially pertains to IT resource planning and support capability among existing systems and data management.

New technologies are always on the horizon, and some will provide meaningful benefits to processes and decision-making. At the same time, supply chain teams have to operate within the existing business system environment that include ongoing and sometimes new challenges related to external and internal data requirements or lack of consistent data standards across multiple tiers of supply or logistics networks.

Change management involves a managed transition, one that includes maintaining the existing and preparing for the future state of capabilities.

It behooves supply chain leaders to ensure that strategies and support resources are adequate to support both maintaining existing and transitioning to the deemed transformational timetable. Advanced technologies take time to garner understanding and prototype testing in determining the most appropriate and meaningful added value for businesses or supply chain management processes. There are ongoing concerns related to the sizing and expense of supporting very large data models as well as adequately training large language models for needed accuracy.

Avoid being surprised or blind sighted that the IT resources needed to support the existing operational needs have suddenly gone away to prepare for the future state. Especially when that future state remains uncertain.

Yes, IT support resources can be contracted for transitional periods, but the tribal supply chain and systems knowledge cannot.

That is where Gen AI is supposed to make its mark.

 

Bob Ferrari

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