How IKEA, JP Morgan are Upskilling Thousands of Employees for AI

⏱️ Your Friday Brief (TL;DR)

Welcome back, decision makers!

This week, we look at traditional industries diving headfirst into the AI deep end. From JP Morgan's quarter-million employees using AI daily to IKEA training 30,000 workers on prompt engineering, the message is clear.

• BCG on using AI in Banking KYC

• How luxury fashion house LVMH is adopting AI

• IKEA’s AI Transformation

• A look at how JP Morgan’s 250,000 employees use AI

Let’s dive in 🤖

🚀 JP Morgan's Quarter-Million Employee AI Army

The GPTLDR

Nearly 250,000 JP Morgan employees have access to their proprietary LLM Suite platform, with just under half using gen AI tools every single day. Backed by an $18 billion annual technology budget, the bank is demonstrating what "AI-first" actually looks like at enterprise scale.

The Details

• The bank's gross benefit from AI efforts has been growing steadily at about 30-40% per year.

• JP Morgan’s Two-pillar strategy: Top-down approach focusing on domains with transformative value (credit, fraud, marketing) plus bottom-up federated innovation through self-service tools.

  • An LLM Suite evolved from a chatbot to a full ecosystem. "an AI-connected enterprise with powerful AI intelligence connected to team knowledge systems, firm-wide data, and applications".

  • New job categories emerging: prompt engineers evolving into "context engineers" who get all needed context into AI systems for right decisions

Takeaways

The Six Pillars of the Agentic Enterprise:

1. Adaptive Strategy – Treat autonomy as a core business transformation, not an IT project.

2. Proactive Risk, Security & Governance – Introduce “guardian agents” and policy-as-code to maintain trust.

3. Intelligent Data Ecosystem – Build unified, vectorized data fabrics that feed real-time decisions.

4. Scalable Tech Enablement – Move from APIs to MCP/A2A (Model Context & Agent-to-Agent) architectures.

5. Empowered Workforce – Redesign roles around orchestration, oversight, and creativity; new roles emerge like “Agentic Process Strategist.”

6. Ongoing Change Management – Focus on workforce trust, transparency, and brand reputation in an era of algorithmic decision-making.

🎯 BCG’s Data Foundation Playbook for AI Success

The GPTLDR

75% of AI transformations and 95% of GenAI initiatives stall, and leaders consistently point to lack of trustworthy data as the primary challenge. BCG's white paper reveals that successful GenAI implementation isn't about the models — it's about building an AI-native data platform that can actually feed them.

The Details

GenAI has sparked bottom-up innovation with employees building their own AI-powered productivity apps, but without robust data foundations, these remain demos rather than enterprise-grade solutions

Four critical components for success:

1. Discoverable Data: Using specialized LLMs that can infer schema, identify relationships, and extract semantic meaning from both structured and unstructured sources.

2. Zero-Trust Access Control: IBM research reveals 97% of breached AI systems lacked proper access controls, with shadow AI breaches costing organizations an additional $670,000 per incident.

3. Semantic Infrastructure: Formal ontologies become strategic assets rather than academic exercises — defining how your organization understands its world.

4. API Management: Clean, documented, and uniformly accessible internal APIs are essential for LLM function calls.

Why It's Important

• Foundation determines ceiling — No amount of clever prompting saves bad data architecture.

• Security is existential — One shadow AI breach can cost you $670K and untold reputation damage.

• Time to value accelerator — Proper foundations mean the difference between endless POCs and production-ready AI.

Software sprawl? That’s SaaD.

Software was supposed to make work easier. Instead, most teams are buried under it.

That’s SaaD – Software as a Disservice. Dozens of disconnected tools waste time, duplicate work, and inflate costs.

Rippling changes the story. By unifying HR, IT, and Finance on one platform, Rippling eliminates silos and manual busywork.

• HR? One update applies to payroll, benefits, app access, and device provisioning instantly.

• Finance? Close the books 7x faster with synced data.

• IT? Manage hundreds of devices with a single click.

Companies like Cursor, Clay, and Sierra have already left outdated ways of working behind – gaining clarity, speed, and control.

Don’t get SaaD. Get Rippling.

Is SaaD hurting you?

🤖 IKEA's Full-Stack AI Transformation 

The GPTLDR

IKEA parent Ingka Group has plans to train 30,000 employees in AI literacy, IKEA is proving that traditional retailers can successfully transform into AI-native organizations.

The Details

• Since FY24, IKEA has set targets to provide AI literacy training to approximately 30,000 co-workers and 500 leaders

• Concrete implementations include:

  • AI-powered stock-counting drones providing real-time inventory updates, enabling proactive stock replenishment.

  • Demand Sensing AI tool that leverages up to 200 data sources per product, considering factors from weather forecasts to festival purchasing preferences.

  • IKEA AI Assistant launched in OpenAI GPT Store, helping customers with product selection and availability.

  • "Hej Copilot" internal tool with Microsoft for image creation and presentation building.

What They Did DifferentlWhy It’s Important

• Proof that legacy can transform — If a 80+ year-old furniture retailer can do it, what's your excuse?

• Sustainability meets profitability — 30% emissions reduction while growing revenue proves the false dichotomy

• Employee-first approach works — Training 30,000 workers creates internal momentum versus top-down mandates

📚 Interesting Reads

• McKinsey explores how procurement functions are leveraging AI to move from cost centers to strategic value creators, with early adopters seeing 15-20% efficiency gains.

• The Economist deep-dives into luxury fashion houses "rewiring the maison" — how heritage brands are quietly embedding AI while preserving the human craft narrative.

• CIO's change management guide for AI agents tackles the organizational shift from managing people to managing digital workers.

• MIT Technology Review unpacks the AI adoption riddle — why companies with the most to gain from AI are often the slowest to adopt it.

• CIO explains context engineering, the evolution beyond prompt engineering that JP Morgan calls the next critical job family.

• CIO's roundup of 20 AI workflow tools for adding intelligence to business processes — your Monday morning shopping list for operational AI.

 ➜ Until Next Week

A couple lessons from JP Morgan and IKEA to end off the week. Use an opt-in approach rather than mandates, creating "fear of missing out”. Little actions can help teams build AI into their workflows, from creating prompt libraries, "prompt of the week" emails, and social channels internally. Make the late adopters ask why they don't have access yet. FOMO drives adoption faster than any McKinsey framework ever will.

Stay curious,

—The GPTLDR Team

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