Observed Signal · Mar 26, 2026 · Policy Update · Source: Digiday · Impact: 2/5 · Sentiment: Neutral
Lowe’s Fights AI 'Sprawl' with Governance and Guardrails
Lowe’s is rolling out and governing multiple AI agents across customer and employee experiences while trying to avoid what it calls “AI sprawl” — poorly coordinated, siloed agents that are hard to maintain. The retailer launched Mylow, a customer-facing virtual assistant, and Mylow Companion, an employee-facing assistant, and has created an AI transformation office plus a Lowe’s-built AI foundry that provides observability and explainability. Lowe’s uses a human-in-the-loop approach, layered technical guardrails, and a four-parameter business-case review (ROI, capital investment, risk, and change leadership) to decide where to deploy agents. The company reports roughly one million AI-driven questions per week across consumer and employee tools, about 300 basis points improvement in net promoter score since rollout, and emphasizes partnering with major AI providers and hiring specialized talent.
Provides practical retailer-level details on AI agent governance, human-in-loop frameworks, observability and measured customer impact — relevant to retail martech but not industry-shifting.
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Key Takeaways & Evidence Grounding
- Lowe’s released Mylow, a customer virtual assistant, in March of last year.
- Lowe’s announced Mylow Companion, an employee-facing AI tool, in May of last year.
- Lowe’s created an AI transformation office and a Lowe’s-built AI foundry with observability and explainability features.
- Lowe’s reports about one million AI-driven questions per week and ~300 basis points improvement in net promoter score since rollout.
- Lowe’s operates roughly 1,700 stores and has about 450,000 associates; stores are cited as ~100,000 square feet each.
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Lowe's Uses AI to Boost DIY Online Conversions
Lowe’s told investors on its Q1 2026 earnings call that AI investments are improving online sales and in‑store customer metrics. CEO Marvin Ellison said customers who use the MyLowe AI shopping assistant convert at three times the rate of non‑users; MyLowe handles more than 1 million inquiries per month. An associate-facing tool, Mylow Companion, was cited as driving a 2% lift in in‑store satisfaction when used. Lowe’s is also adding loyalty and services features for DIY customers, including the March launch of the paid HomeCare+ subscription (two in‑home visits per year). Comparable sales rose 0.6% year‑over‑year in Q1 2026 and net sales were $23.1 billion, up 10.3% year‑over‑year.
Retailers Embrace AI, Set Boundaries
At the CommerceNext Growth Summit in New York City, retail and brand executives described how they are deploying AI across customer-facing and internal operations — while clearly defining use-cases they won’t automate. Speakers from Tecovas, Ulta, Pandora, JD Finish Line, Kendra Scott and Authentic Brands Group described implementations such as in-store associate assistants, AI-driven product information tools, customer-service agents that escalate to humans, propensity modeling to route inquiries, and brand-specific knowledge bases. Executives emphasized human-in-the-loop controls for customer interactions, refused AI-driven model/on-skin imagery for product photography, and highlighted how first‑party customer data and machine learning are being used to personalize experiences and surface insights from call-center data.
Retailers curb shadow AI but face agentic sprawl oversight
A report from security firm Netskope reveals that retailers are improving governance of employee AI tool usage, but face new challenges from agentic AI sprawl. The share of retail employees using ungoverned AI tools fell from 70% to 44%, while approved tool usage rose from 40% to 73%. However, nearly all employees use software with embedded AI features, and 90% use AI tools trained on customer data. Netskope observed a 400% increase in retail-sector AI agents interacting with remote Model Context Protocol (MCP) servers, raising data exposure risks. Regulated data was involved in 56% of AI-related policy violations. The report recommends improved visibility, traffic inspection, and data-loss-prevention policies to mitigate risks.
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