Why Partner With Resilience Technologies
A position paper on how we approach technology consulting — and why it's different from what the largest firms are selling right now.
The consulting industry is in the middle of an AI gold rush. Clients are being asked to commit to platforms, licenses, and enterprise-wide agent rollouts before anyone has asked the basic question: does your business actually need this? We built Resilience Technologies around a different premise — understand the business first, then design the smallest thing that works.
The problem with the current moment.
In February 2026, OpenAI launched Frontier Alliances — a formal partnership with McKinsey, BCG, Accenture, and Capgemini to push Frontier, its enterprise platform for building and managing AI agents (or "AI coworkers," as OpenAI markets them), into large organizations. McKinsey and BCG handle strategy and change management; Accenture and Capgemini handle implementation. The pitch is that every enterprise needs a fleet of these agents embedded across its workflows, and these firms will help you plan, build, and manage that fleet.[1]
The incentives here are worth naming. When a large consulting firm partners with a platform vendor, the engagement model shifts from "solve your problem" to "deploy the platform." The firm earns fees on strategy, implementation, and change management. The vendor earns platform revenue. Both sides win when you buy more. Whether you needed more is a separate question — one that doesn't always get asked.
This isn't new. The same pattern played out with ERP rollouts in the 2000s, big-data platforms in the 2010s, and "digital transformation" for most of the last decade. What's different now is the speed and the marketing pressure. Executives are being told that if they don't deploy AI agents this quarter, they'll be left behind.
What the data actually shows.
of enterprise GenAI pilots deliver no measurable P&L impact
MIT's 2025 report The GenAI Divide: State of AI in Business analyzed 300 public AI deployments, surveyed 153 leaders, and interviewed 52 executives. It found that 95% of pilots produced no measurable return. Roughly $30–40 billion in enterprise investment has been deployed against that 95% failure rate.[2]
of custom enterprise AI tools ever reach production
The same study found that the vast majority of internal AI builds stall before they ship. The successful 5% share a common trait: they solved a specific, bounded back-office problem before they attempted anything more ambitious.[2]
of GenAI budgets go to sales & marketing — the wrong place
More than half of enterprise GenAI spend is directed at sales and marketing tools. MIT's finding: the highest-ROI applications are actually in back-office automation — eliminating outsourced processes, cutting agency fees, and streamlining operations. In other words, the money is chasing the headline while the real wins sit unclaimed.[2]
The root cause isn't talent or infrastructure
MIT concludes that the core barrier is learning, not technology. Most deployed GenAI systems don't retain feedback, don't adapt to context, and don't improve over time. They get dropped into workflows as if they were finished products. They aren't — and buying a bigger platform doesn't fix it.[2]
How we work instead.
We built Resilience Technologies as a deliberate counter to the playbook above. No platform allegiance, no preferred vendors, no pressure to upsell. Our engagements start with the business in front of us and end when the problem is actually solved.
Start with the business, not the platform
Discovery comes first. We spend real time with operators — not just executives — to understand how the work actually runs, where the real cost sits, and what's breaking. No tool gets named until the problem is defined.
Right-size, and say no when appropriate
If the smallest thing that works is a SQL query and a scheduled script, that's what we'll recommend. If you don't need AI, we'll tell you. Our job is to solve the problem in front of us — not to maximize scope.
No reseller kickbacks, no platform quotas
We hold no vendor rev-share agreements and no quarterly platform targets. When we recommend a tool, it's because it fits your constraints — not because someone is paying us to place it.
Prototype over proposal, then stay
We'd rather ship a rough working prototype against your real data than produce a 60-page deck. Then we stay through the iterations — maintenance, migrations, expansion — as the technology you need at 20 people becomes the technology you need at 200.
References.
- Fortune — "OpenAI partners with McKinsey, BCG, Accenture, and Capgemini to push its Frontier AI agent platform" (February 2026). fortune.com/2026/02/23/openai-partners-with-mckinsey-bcg-accenture-and-capgemini. Also covered by TechCrunch and Inc.
- MIT NANDA / Project NANDA — The GenAI Divide: State of AI in Business 2025. Summarized by Fortune, Healthcare IT News, and The Financial Brand.
Let's have the conversation they're not having
If you're being pitched an AI rollout and you're not sure it's the right move — or you want a second opinion that isn't attached to a platform — we'd rather talk you out of the wrong project than sell you the wrong one.
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