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Retailers Increasing Demand for Warehouse Automation

More than two-thirds of customers are resorting to omnichannel buying – online orders have sky-rocketed by more than 28 percent. 
Unlock the potential of your physical stores and integrate them with your ecommerce platform: it is the biggest digital transformation opportunity for retailers right now. Learn how investments in warehouse automation can enable this digital journey.

Digital Drives E-commerce for Modern Retailers

As trends emerge, evolve and fade, you work hard to win and maintain the loyalty of mercurial buyers. Customer personalization, safety and convenience are top of mind, as is the move to ecommerce and omnichannel buying.  

Whether you are designing your ecommerce strategy or addressing supply chain or inventory challenges, lean on ISG’s market-leading data to inform your decision-making. ISG can assess your current state operating model and design and create sourcing strategies to lower your operating costs. We’ll also uncover opportunities for immediate cost optimization and asset monetization to fund customer-facing digital transformation. ISG will work with you to strengthen your internal controls and improve your overall operational performance so you can focus on what is most important – attracting and keeping customers and building your market share.

The market has moved from ambition to accountability.

AI investment is accelerating, but results remain uneven. Only one in four initiatives is meeting revenue impact expectations, at an average spend of $1.3M per use case. Enterprises are no longer asking whether AI works. They are being asked to prove that it pays.

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What We Deliver

ISG turns AI complexity into measurable execution advantage — from strategy and governance through to commercial models, workforce readiness and independent market intelligence.

Autonomous Enterprise
ISG helps organizations redesign operations for an autonomous future, defining where AI agents deliver the most value, restructuring workflows around them and building the accountability models that keep autonomous execution governed and auditable. As agentic AI moves from emerging capability to operational reality, the enterprises that win will be those that redesigned for it before it arrived.
Autonomy-Level Pricing
ISG's Autonomy-Level Pricing framework gives enterprises transparent, benchmarkable commercial structures that reflect how AI-enabled services are actually executed. By tagging each resource unit with the autonomy level used to deliver it, from human-validated to fully autonomous, ALP ensures that pricing evolves alongside capability and that both buyers and providers can quantify the value of advancing AI maturity.
AI & Software Intelligence
Drawing on the analysis of more than $2.6 billion in tracked AI spend through ISG Provider Lens and ISG Buyers Guide research, ISG gives procurement, technology and finance leaders the independent intelligence they need to make sharper build-versus-buy decisions, rationalize vendor portfolios and hold providers accountable to measurable outcomes.
AI Governance
ISG helps enterprises shift from compliance-as-constraint to governance-as-operating-model, embedding controls at the point of data creation, defining accountability for autonomous actions and building adaptive frameworks that keep pace with AI without slowing it down. Enterprises that get this right don't just manage risk. They build the trust that lets them scale faster.
AI Strategy
ISG grounds AI strategy in what is actually working, drawing on research across 1,200 enterprise use cases to align investment to where impact is most achievable. We help leadership teams design the data, talent and governance foundations that move AI from isolated pilots into the workflows that drive commercial results.
AI Maturity Index
The ISG AI Maturity Index delivers a scored, benchmarked assessment of AI readiness in 15 minutes, calibrated against peers across 75 countries and focused on the dimensions that determine whether AI investment translates into business results. Organizations receive dimensional analysis, gap identification and a personalized growth roadmap.
The market today

Enterprise AI has moved out of IT and into the revenue line.

AI investment is shifting decisively toward revenue-generating functions. CRM automation, sales enablement and forecasting have replaced chatbots and IT productivity tools as the leading use case priorities, reflecting enterprise recognition that productivity gains alone do not satisfy board-level scrutiny. At the same time, use cases in production have doubled since 2024, and the portfolio is diversifying rapidly, with over 300 distinct function and industry-specific use cases now in active deployment.

ISG research across 1,200 enterprise use cases shows that the strongest AI returns are currently concentrated in compliance, risk management and quality control, not in the growth and cost outcomes most enterprises originally set out to achieve

The gap between where enterprises are investing and where AI is actually delivering is the defining commercial tension of 2025. Organizations that close it by targeting functions with structured, revenue-attributable data and clear ROI measures will establish performance benchmarks that compress the window for competitors still cycling through pilots. The standard is being set now.

Where enterprises are feeling the pressure
  • Business outcomes are lagging AI ambition
    Enterprises are scaling Al faster than they are realizing value from it. The number of use cases in production doubled between 2024 and 2025, yet only one in four initiatives is meeting revenue impact expectations, and broad cost savings remain elusive. At an average spend of $1.3M per use case, the ROI gap is sharpening board-level scrutiny and forcing a harder question: are we building Al for impact, or for activity?
  • Data infrastructure is exposing years of deferred investment
    Al does fail in isolation. It fails on the foundations beneath it. Most enterprises are running modern Al on architectures built for reporting and compliance. Generative and agentic Al demand real-time contextually rich, governed data at the point of use. Without it, pilots stall and value dissipate before it reaches the business.
  • The barrier to scale is organizational, not technical
    Organizational readiness as the bigger constraint on Al adoption, not talent or tooling. Workflows haven't been redesigned. Decision rights haven't shifted. Enterprises that treat Al as a pure technology deployment, without investing in the human side of adoption, consistently report underwhelming ROI.
  • Agentic AI is outpacing governance
    As Al moves from generating outputs to executing tasks autonomously, the governance gap widens. Agentic Systems introduce a new class of risk that static compliance frameworks were never designed to catch. Governing what Al does, not just what it produces, is now a business-critical requirement.
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