When QXO Inc. announced the appointment of Ashwin Rao as its first chief artificial intelligence officer in November, it became one of the first distributors in the building products sector to formally add AI leadership to its executive suite. The move reflects how artificial intelligence is no longer just a tool for tech firms — it’s becoming a core operating discipline for industrial, manufacturing and distribution companies, modernizing how they run their businesses.
Brad Jacobs, chairman and CEO of QXO, said that artificial intelligence will permeate everything the company does, “including demand forecasting, inventory management, and ecommerce. Ashwin is recognized as one of the brightest minds in enterprise AI. He will be instrumental in making QXO the most tech-forward company in the industry.”
Rao said: “The opportunities to use AI to transform the building products distribution industry are endless. I’m excited to get started on dozens of AI workstreams that, combined with advantages of scale, will help QXO increase efficiency, optimize supply chains, and add value for our customers.”
Rao’s career spans more than three decades at the intersection of data, finance, and technology. Before joining QXO, he served as Target Corp.’s first head of artificial intelligence, leading model-driven initiatives across pricing, merchandising, customer experience, and logistics. He also held senior quantitative modeling roles at Goldman Sachs and Morgan Stanley.
For an $800 billion market built on supply chains, trucks, and physical inventory, QXO’s decision signals a major shift: AI is becoming an executive-level mandate in distribution.
Protolabs Adds Chief Technology and AI Officer
Digital manufacturing company Protolabs Inc. is among a growing number of industrial firms elevating artificial intelligence to the executive level. The Minnesota-based company recently named Marc Kermisch as its new chief technology and AI officer, succeeding Oleg Ryaboy, who departed after three years in the role.
Kermisch will oversee Protolabs’ global technology organization, including its AI strategy and digital manufacturing platforms. The appointment reflects how manufacturers are merging technology and artificial intelligence under unified leadership to accelerate automation, product development, and customer responsiveness.
“As we look ahead, technology will continue to drive our manufacturing innovation and support our long-term goal of providing end-to-end prototyping-to-production capabilities for customers,” said Suresh Krishna, president and CEO of Protolabs.
Kermisch brings more than 25 years of experience leading technology, research and development initiatives in manufacturing, software, and retail. Most recently, he was chief technology officer at Emergent Software, a Minneapolis firm specializing in software development, cloud transformation, and AI solutions. Before that, he served as global chief digital and information officer at Case New Holland, a $20 billion manufacturer of agricultural and construction equipment, where he led projects in autonomous vehicles, precision farming, and electric powertrains.
He has also held executive roles at Optum Rx, Bluestem Brands and Red Wing Shoe Co., and serves on the boards of American AgCredit and Crew Carwash.
“Protolabs has built a strong digital foundation that runs through every part of its operations,” Kermisch said. “Expanding that through new software and AI capabilities presents a significant opportunity to enhance speed, quality and efficiency across the manufacturing process.”
Protolabs provides digital manufacturing services including 3D printing, CNC machining, sheet metal fabrication, and injection molding for industries such as aerospace, automotive, health care and consumer products. Its decision to combine technology and AI leadership underscores how digital manufacturers are embedding intelligence into every stage of production — from design to delivery.
The Emergence of the Chief AI Officer
Just a few years ago, few companies outside Silicon Valley had executives dedicated exclusively to artificial intelligence. Today, the title of chief AI officer (often abbreviated as CAIO) is entering the mainstream.
According to a 2024 study by the MIT Sloan Management Review, about 11% of global enterprises already have a chief AI officer, and another 21% are actively searching for one. Dell Technologies estimates that more than 120 companies worldwide have created CAIO positions — triple the number in 2020.
Yet among wholesale distributors, such appointments remain rare. Most large national players still delegate AI responsibility to their chief information officer or chief technology officer. That makes QXO and Protolabs early movers in formalizing AI as a stand-alone function reporting directly to the top.
Why the Role Exists
The chief AI officer sits at the intersection of business strategy, data science, and organizational change. This position exists because AI now touches every process in a modern enterprise.
In industries such as distribution and manufacturing, the CAIO’s responsibilities typically include:
Setting the AI strategy. Identifying high-impact use cases — such as forecasting, logistics optimization, dynamic pricing, or customer service — and sequencing them for rollout.
Building infrastructure and data foundations. Ensuring that data from enterprise resource planning, warehouse and transportation systems is standardized, accessible and ready for model training.
Operational integration. Embedding AI into daily operations, from procurement and order routing to ecommerce search and customer communications.
Governance and risk management. Overseeing model transparency, bias mitigation, and compliance with emerging AI regulations.
Across sectors, the CAIO’s mission is to turn data science into measurable business outcomes.
Why Distribution and Manufacturing Need a CAIO
Wholesale and distribution firms have historically lagged in digital transformation. Many still operate on legacy systems and manual workflows. AI is changing for several reasons.
Tight margins. Distributors often operate on margins around 5%. Predictive analytics can reduce excess inventory, improve demand forecasting, and boost profitability.
Ecommerce growth. B2B digital sales in the United States are projected to exceed $2 trillion by 2026. AI-driven recommendations, search relevance, and chat automation are becoming essential to compete with platforms such as Amazon Business and Zoro.
Labor and logistics efficiency. AI can optimize delivery routes, truck loading, and warehouse layouts, reducing costs in labor-intensive operations.
Supplier and tariff risk. Predictive models can analyze supplier performance, lead times, and geopolitical trends to forecast disruptions or tariff exposure.
Regulatory alignment. With the European Union’s AI Act and similar frameworks emerging globally, companies automating pricing or logistics will face new compliance requirements. The CAIO is the natural executive to manage that oversight.
In short, AI can improve every performance metric that matters — margins, inventory turns, delivery times and customer satisfaction — but only with leadership that understands both algorithms and operations.
Inside the Chief AI Officer’s Work
The CAIO’s job combines strategic planning with technical execution. A typical day may include leading data-science teams, approving AI vendors, designing governance frameworks, and briefing the board on progress.
In manufacturing and distribution, early initiatives often focus on:
- Demand forecasting: Using sales, weather, and economic data to improve order predictions.
- Inventory optimization: Deploying dynamic replenishment systems that minimize stockouts and reduce carrying costs.
- Pricing management: Adjusting prices in real time based on cost inputs and competitive data.
- Warehouse automation: Applying computer vision and predictive maintenance to material-handling equipment.
- Customer experience: Using AI-powered chatbots and virtual assistants for order tracking and quote generation.
Each initiative requires coordination across departments — information technology, finance, sales, and operations — reinforcing the need for executive-level accountability.
Pay Reflects the Stakes
Chief AI officers are among the best compensated executives. According to Equilar’s 2025 Executive Compensation Study, AI leaders at large corporations earn median total pay of $1.6 million, including bonuses and equity. Glassdoor lists the average base salary for U.S. CAIOs at about $350,000, while Comparably places total compensation between $250,000 and more than $1 million, depending on company size and industry.
At smaller or privately held firms, total cash compensation ranges from $250,000 to $400,000, with equity often playing a larger role. Analysts note that these levels now mirror those of chief technology officers and chief operating officers, underscoring how boards view the CAIO not as a technical specialist but as a growth-driving executive.
A Turning Point for Distributors and Manufacturers
QXO’s elevation of AI leadership to the same level as finance and operations reflects a broader shift in mindset across industrial markets. Companies that once viewed digital tools as IT projects now see them as business imperatives.
QXO plans to become a technology-driven leader in building products distribution through acquisitions and organic growth, with AI as its strategic lever. Rao’s appointment consolidates that goal into a single executive mandate.
Protolabs’ combined technology and AI role similarly shows how digital manufacturing is evolving beyond experimentation. For both companies, AI is no longer optional — it’s foundational to how they compete.
The Broader Trend
Across industries, the number of chief AI officers is climbing rapidly. Studies published over the past 18 months show double-digit growth in CAIO appointments among public and private companies. Although fewer than 200 CAIOs exist globally, adoption is accelerating, especially in manufacturing, energy, and logistics.
The trend mirrors earlier corporate shifts. Two decades ago, few companies had chief digital officers. Today, digital strategy is embedded in every enterprise. The same evolution is happening with AI.
What Comes Next
For distributors and manufacturers, naming a chief AI officer is more than a branding exercise — it formalizes accountability for AI strategy, governance, and measurable outcomes. It also signals to investors and employees that artificial intelligence is central to the company’s future.
As early adopters like QXO and Protolabs show, AI leadership is now a defining feature of industrial modernization. The chief AI officer is emerging as the executive who integrates physical operations with digital intelligence — the person who will shape how the next generation of distributors competes.
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