What ready mixed concrete jobs will look like after the AI bubble pops.
Economic booms and subsequent busts, especially those associated with innovation, have been a part of history for centuries. So what should we expect as the wax (hype) starts to wane for generative artificial intelligence (AI) powered by large language models a la ChatGPT? The likely answers will surprise you.
Surprise No.1: AI is not new. In the 1940s, John von Neumann proposed a universal constructor—a self-replicating machine that could be used to build additional machines—and provided the theoretical underpinnings for its construction. But, until the recent advances in computer chip power, applied AI was relegated to dabbling and science fiction stories epitomized by the likes of The Terminator and Kurt Vonnegut’s Player Piano: A Novel.
But first, let’s discuss bubbles.
A bubble of note
During the 1840s, new technology emerged in the U.K. that put modern railway travel within reach. The potential economic impact was ginormous, and numerous new companies were formed to lay track and provision trains. The fledgling entities were racing against each other and desperately needed working capital to secure the all-critical “first mover advantage” for establishing a track network.
Wealthy Britons were eager to invest and share in the perceived inevitable rewards. Luckily (or not) for them, the British government had relaxed its prohibition on share trading in 1825 to create a functional stock market. Huge wealth was poured into hundreds of newly minted rail companies busily buying land and laying track, surging their stock prices to stratospheric levels.
The inevitable bust happened, with most rail companies failing. All was lost to the investors, but not all was lost. Enormous miles of inner-connected track had been hewed out and subsequently consolidated by the few remaining winners who harvested the rewards for propelling the U.K. into the world’s most modern and powerful economy.
The hype cycle
Market intelligence firm Gartner promoted the term “hype cycle” for the life cycle of new technologies. According to the Gartner hype cycle, most innovations, services, and disciplines will progress through a pattern of overenthusiasm and disillusionment (often from too-high expectations), followed by eventual enlightenment and productivity. Does it sound a bit like the U.K.’s railroad mania?
American organizational theorist and management consultant Geoffrey Moore speaks to that brand of disillusionment in his classic book on technology marketing, Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers. Gaps in adaptation occur as technology moves from enthusiastic innovators and early adopters to more pragmatic and/or cautious consumers who are less enamored by what’s new and more concerned with usefulness or ease of use.
Surprise No. 2: The technology hype cycle by any name is genuine and, despite its bumpy path, will impact long-term economic prosperity.
La bulle du jour
Microsoft is savvy and painfully knows the history of disruptive innovation, mainly because it has missed out countless times over the past two decades. Seeing the long-term potential of AI and being burdened with too much cash, they carved off a paltry $10 billion to secure the first mover advantage by snapping up ChatGPT and its developer, OpenAI. Think of it as hewing out the tracks ahead of the competition.
Microsoft fired the first major shot, and like the Oklahoma Land Rush of 1889, it unleashed a stampede of investors. The paradox is that for most investors, artificial intelligence’s valuation has been inflated by greed-infused stupidity. Hence, the bubble.
The phoenix of useful AI in RMC
Substantial, long-term changes to the world around us will undoubtedly emerge from the ashes of the pending crash of AI stocks. Changes to the fulfillment process for real-time and structural ready mixed concrete (RMC) will happen, whether we like it or not. Let’s discuss a few probable impacts regarding the most pressing current profit leaks.
Surprise No.3: AI’s role in refactoring labor and productivity will immediately and significantly impact our industry. Entire classes of workers will no longer be needed, and the number of others will be reduced.
- Finance: The ongoing digital enterprise transition is expediting workflow management and democratizing access to information. Nowhere is this more apparent than in finance. AI will put this on steroids with the ability to make routine but highly complicated decisions concerning the worthiness of customers, what work-type segments to seek, and dispute resolution.
- Sales: Most customers will be able to self-quote based on what, when, and where the material is being ordered, combined with their past behavior. Salespeople will cease being expediters for jobsite problems, as all customer information and communication will be intuitively handled with AI.
- Logistics: Dispatchers will become supervisors, as AI will provide the vast majority of scheduling, inventory replenishment, and diversions. Routine customers will be able to directly secure dispatch time slots as part of the online ordering process.
- Quality control: AI will craft mixes to minimize cost and/or their carbon dioxide footprint. Each batch design will be optimized with feedback from onboard truck sensors, truck dosing, anticipated traffic delays, and weather.
- Building Information Modeling: BIM systems will finally overcome their own disillusionment phase, with AI wrangling all the constantly changing, intractable details. AI will result in a fully automated BIM system that can order RMC from a fully automated dispatch system in coordination with all other materials and services. The phrase, “Look, Mom, no hands!”—with all the associated peril—comes to mind.
Crossing the chasm
The unbridled hopes and aspirations heaped upon AI today are doomed to fall short. While what will emerge will power huge economic gains in all aspects of the economy, there will be losers. As trains in the U.K. displaced bargemen and teamsters during the 1840s, AI will significantly alter tomorrow’s employment landscape. The key takeaway is to accept the inevitability of significant change and prepare as best as we mere mortals can.
Craig Yeack has held leadership positions with both construction materials producers and software providers. He is co-founder of BCMI Corp. (the Bulk Construction Materials Initiative), which is dedicated to reinventing the construction materials business with modern mobile and cloud-based tools. His Tech Talk column—named best column by the Construction Media Alliance in 2018—focuses on concise, actionable ideas to improve financial performance for ready-mix producers. He can be reached at [email protected].