Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesAvnet says it uses AI to improve quoting, customer-service information, engineering, inventory forecasting and supply-chain coordination. CIO Max Chan’s stated test is whether those efforts support a business outcome—not how much the company spends on AI. The interview describes use cases and intended benefits, but reports no quantified Avnet-specific results such as higher conversion, lower inventory or faster service.
How does Avnet use AI?
In a February 11, 2026 interview with CIO, Avnet CIO Max Chan described AI as a way to make information more useful to customers and employees across several business functions. The interview identifies these uses and mechanisms:
| Business function | Stated AI use or value mechanism | What the interview establishes |
|---|---|---|
| Sales and quoting | Assembling pricing, product end-of-life information and country-of-origin information into more complete quotes, more quickly. | Chan links better quotes to customer decision-making and Avnet’s goal of winning business and improving conversion; no conversion, margin or time-saved figure is reported. |
| Engineering | Supporting engineering design. | Named as an area of potential leverage; no system, model or measured result is specified. |
| Inventory and forecasting | Supporting inventory management and forecasting. | Named as areas of potential leverage; the interview gives no forecast-accuracy or inventory-reduction result. |
| Customer service | Making information more readily available to customer-service agents. | Chan describes internal and external use, but no service-quality or handling-time metric is given. |
| Supply-chain orchestration | Connecting customer and partner information with Avnet’s data to support coordination and resilience. | The interview identifies Avnet’s Partner Digital Exchange as a way to bring downstream data together with Avnet data; it reports no quantified supply-chain outcome. |
Data quality connects these examples. Chan said, “Leveraging AI means cleansing data so customers can make the right decisions.” That is his description of the intended role of AI and useful information, not a measured customer-decision outcome.
How does AI help Avnet’s supply chain?
Chan describes supply-chain resilience as depending in part on relationships with customers and partners, data availability and connectivity. Avnet’s Partner Digital Exchange brings downstream data together with Avnet’s own information for orchestration and customer insight, according to the interview.
Windows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOutdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware match#1 Best Overall
The architecture matters because partner coordination requires systems to exchange information. Chan says Avnet moved beyond a monolithic, ERP-centered environment toward a digital- and AI-first architecture, with microservices and strong API connections supporting partner connectivity. The interview does not provide technical specifications or quantify how much this approach improved resilience, availability or delivery performance.
How does Avnet measure AI ROI?
Chan says teams should begin with the business outcome they want, then ask whether an AI-supported change contributes to company strategy. More accurate pricing and a more complete customer quote are examples he gives. He cautions against treating AI return as a standalone calculation of technology spend.
That framing makes the relevant evaluation specific to the process: for quoting, a company might examine quote completeness, accuracy, speed or conversion; for forecasting, it might examine forecast accuracy or inventory effects. These are possible measures implied by the described goals, not metrics Avnet reports using or results the interview establishes.
Chan summarizes the governance principle this way: “Change management is key, but the overall governance of going back to whether something is contributing to a business outcome, or is directly supporting a business strategy, is essential.”
Recommended Free Tools
Rank #3
What business results has Avnet reported from AI?
The CIO interview does not report a quantified Avnet-specific AI return on investment, conversion-rate increase, profit change, forecast-accuracy measure, inventory reduction, service metric or productivity result. Chan describes intended mechanisms and the company’s approach; the interview does not independently measure causal impact.
Broader survey figures cannot fill that gap. In McKinsey & Company’s survey fielded March 26–April 5, 2019, 63% of respondents reported AI-related revenue increases in business units where AI was used, and 44% reported cost savings in units where it was deployed. Those are respondent reports from 2019—not current market measurements or evidence of Avnet’s results. The survey had 2,360 participants; 1,872 said their companies had piloted or embedded AI. McKinsey also reported that 58% said their organizations had embedded at least one AI capability in a process or product in at least one function or business unit, up from 47% in 2018.
McKinsey’s 2019 “high performers” were a defined subset: companies reporting AI use in at least five business activities and average revenue increases and cost decreases of at least 5% in units using AI. That group represented 54 respondents, or 3% of respondents reporting company AI use. Among those high performers, 72% said their company aligned AI strategy with corporate strategy, compared with 29% of other AI-using respondents; 65% versus 20% reported a supporting data strategy. These comparisons describe survey respondents, not Avnet.
What people and controls support Avnet’s AI work?
Chan groups Avnet’s AI tools into three categories: productivity tools such as ChatGPT, AI features embedded in software the company already uses, and capabilities developed by his team. He says employees can request tools through a governance process or receive an approved alternative.
He also identifies change management, workforce upskilling and learning agility as implementation needs. Avnet explores whether end-to-end processes could become more autonomous, then brings people back into the loop to augment the process. The interview does not specify which processes are autonomous or how human review is applied in individual use cases.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
