Hanesbrands (HBI): Infosys AI Overhaul or Gildan Merger-What Drives Value Now?

Will Infosys' AI-First Partnership Redefine HanesBrands' (NYSE:HBI) Operations?

HanesBrands has signed a ten-year partnership with Infosys to modernize its IT backbone and embed automation and AI across the enterprise. For operations leaders, this is a signal: the company is committing to system-level efficiency and data-driven execution, not one-off fixes.

The move matters, but it sits alongside a larger variable - the proposed merger with Gildan Activewear. Execution on both fronts will decide whether margin improvements stick and whether the business can absorb demand shifts without breaking cadence.

What the 10-Year Deal Means for Day-to-Day Operations

• Core systems modernization: Consolidate and upgrade ERP, order management, and planning tools; move workloads to scalable cloud; reduce custom code that slows change.
• Data foundation: Establish a single data model, master data governance, and near-real-time visibility from factory to shelf.
• Automation at scale: Build an automation backlog (RPA + workflow) for order-to-cash, procure-to-pay, and record-to-report. Target repeatable tasks first.
• AI use cases: Demand forecasting, inventory optimization, dynamic allocation, production scheduling, quality inspection, pricing, and customer service deflection.
• Global service model: 24/7 support with standard processes, clear SLAs, and cost transparency.
• Change management: Role-based training, frontline adoption metrics, and incentive alignment to usage, not just go-live dates.

Year 1 AI and Automation Use Cases Worth Prioritizing

• Forecast accuracy uplift (SKU/door/region): Reduce stockouts and aged inventory; aim for +5-10 pts improvement.
• Inventory and allocation: Automate replenishment thresholds; raise turns; cut safety stock with guardrails.
• Production and sourcing: Constraint-based scheduling, first-pass yield analytics, and supplier risk flags.
• Order-to-cash: Touchless order entry, auto-match for cash application, and deductions triage.
• Customer operations: AI assistants for ticket routing and knowledge retrieval; deflect low-complexity cases.

KPIs to Track if This Is Working

• Gross margin +150-300 bps from mix, markdown control, and waste reduction.
• Inventory turns +10-20%; aged inventory down 20-30%.
• Forecast error (MAPE) -20-30% on priority SKUs.
• OTIF +3-5 pts; fill rate +2-4 pts.
• OEE +5-10 pts; first-pass yield +2-4 pts.
• Automation hours saved; manual touches/order; days sales outstanding -3-7 days.
• IT run-rate cost/unit down 10-15% over 24-36 months.

Execution Roadmap (0-12 Months)

• 0-30 days: Define value pools and KPIs; freeze a single process taxonomy; stand up a transformation PMO with Ops, IT, Finance, and HR.
• 30-90 days: Baseline data quality; publish automation backlog; select pilot plants/DCs; implement MDM policies and access controls.
• 90-180 days: Launch 3-5 pilots (forecasting, allocation, O2C); codify playbooks; measure lift vs. control groups; retire duplicative tools.
• 6-12 months: Scale wins; renegotiate vendor contracts; embed usage targets into manager scorecards; publish monthly value realization reports.

Where the Gildan Proposal Fits

The near-term catalyst remains the proposed merger with Gildan Activewear. If approved and executed well, it could compress the timeline for value creation - and magnify integration risk.

• Synergy levers Ops can control: SKU rationalization, network redesign, joint S&OP, procurement category savings, and shared services consolidation.
• Decision gates: Common data model, unified planning calendar, product lifecycle governance, and a single performance dashboard for the combined entity.
• Integration risk: Dual ERPs, duplicate SKUs, and conflicting service levels can erase savings. Lock standards before scale-up.

Key Risks for Operations Leaders to Hedge

• Top-line pressure in US intimates: Protect margin with mix control, dynamic markdowns, and inventory discipline.
• Fixed-cost exposure in international markets: Use scenarios for volume dips; deploy flexible labor and variable logistics contracts.
• Data debt: Poor master data kills AI lift. Fund stewardship and data contracts early.
• Vendor lock-in: Keep modular architectures and exit clauses; avoid customizations that block portability.
• Change fatigue: Pace waves, not projects; tie adoption to incentives; measure behavior, not attendance.
• AI governance: Establish quality, bias, and security standards before scale. See the NIST AI RMF for practical guidance here.

The Investor Math (Why Ops Execution Matters)

HanesBrands' narrative points to about $3.6B in revenue and $274M in earnings by 2028. That implies a roughly 0.4% annual revenue decline but a $104M earnings lift from ~$170M today.

A model-based fair value of $6.26 per share suggests a ~3% downside to the current price, with community estimates spanning $6.26 to $8.03. Hitting the earnings line with flat-to-down revenue puts the burden squarely on operations - margin capture, working capital discipline, and cost-to-serve reductions.

Decision Checklist for HBI Operations

• Publish a value tree linking each use case to margin, working capital, or cost-out; review monthly.
• Name accountable owners for data quality in each domain (item, customer, supplier, location).
• Create a unified S&OP cadence and lock a single demand signal for supply, finance, and merchandising.
• Stand up an automation COE; track hours returned and error rates; prioritize finance and customer ops.
• Pilot before scale; require KPI deltas with control groups; kill pilots that don't move metrics in 90 days.
• For the proposed Gildan deal: pre-plan SKU and platform convergence, not after close - reduce the integration clock.

Want to Upskill Your Team on AI for Operations?

If you're building internal capability to run programs like this, explore practical training for operations teams here or browse automation-focused resources here.

Further Reading

• Infosys' AI-first platform overview: Infosys Topaz

Bottom line: the Infosys partnership gives HanesBrands the scaffolding to systematize efficiency. Whether investors see it in the share price will depend on disciplined execution and, if approved, integration quality with Gildan.