GPT-5.5 lands but the model is not the decision

What GPT-5.5 claims

OpenAI released GPT-5.5 on 23 April 2026. It is the sixth update in the GPT-5 series and the first full retrain since GPT-4.5. OpenAI says it is better at coding, computer use, and research. It arrives six weeks after GPT-5.4.

That is a lot of models in a short space of time. But for most UK businesses choosing an AI platform, the model itself is not the most important factor.

GPT-5.5 is codenamed Spud. OpenAI describes it as a model that can handle messy, multi-part tasks with less guidance. It plans, uses tools, checks its own work, and keeps going until the task is done.

The technical claims are notable. A 1M-token context window in the API. An 82.7% score on Terminal-Bench 2.0, which measures command-line task completion. An 84.9% score on GDPval, OpenAI\u2019s own knowledge-work benchmark covering 44 occupations.

API pricing has doubled. GPT-5.4 cost $2.50/$15 per million tokens. GPT-5.5 costs $5/$30. OpenAI says the model uses fewer tokens to complete the same work, which partly offsets the price increase.

OpenAI\u2019s president Greg Brockman described GPT-5.5 as a step toward a super app combining ChatGPT, Codex, and an AI browser into one service. The company now reports 900 million weekly active ChatGPT users and nine million paying business users.

We have not tested GPT-5.5. These are OpenAI\u2019s claims, not our assessment.

Models are already smart

Here is the thing most businesses overlook. Frontier AI models from OpenAI, Anthropic, and Google are all very capable. Compared to 12 months ago, the improvement is significant. Compared to each other, the gap is narrow and shifts with every release.

GPT-5.5 leads on some benchmarks. Claude Opus 4.7 leads on others. Gemini 3.1 Pro leads on others still. One model pulls ahead for a few weeks. Then another release resets the table.

For a 30-person professional services firm or a 100-person manufacturer, the difference between the top three models on any given Tuesday is not what determines whether AI adoption succeeds or fails.

Chasing the latest model version is not a strategy. By the time you have trained your team on one, the next has already shipped.

The platform is the decision

What matters more than the model is the platform wrapped around it. The model is the engine. The platform is the car.

When evaluating an AI platform for your business, the questions that matter are practical. What tools does the AI have access to? Where can it affect change?

Consider the capabilities that actually shift how people work:

• Connectors. Can the AI reach into your existing tools? MCP connectors, plugins, and integrations determine whether the AI sits in isolation or plugs into your CRM, email, calendar, and file storage. An AI that cannot reach your data cannot change your workflow.
• Workspace agents. Can the AI act on your behalf across applications? Anthropic\u2019s Cowork, OpenAI\u2019s Codex expansion, and Google\u2019s workspace integrations are all moving in this direction. We wrote about this shift when OpenAI expanded Codex from a coding tool into a workspace agent. That release changed more about how people work than any model update did.
• Computer use. Can the AI operate software the way a person would? Navigate screens, fill forms, move between applications. This is where agentic AI starts replacing repetitive screen work.
• Coding and document creation. Can the AI build tools, write reports, create spreadsheets? This determines whether it assists your work or produces it.
• Image generation. Can the AI create visual content inside the same platform? For marketing teams and content producers, this removes a tool switch.

Each of these capabilities exists independently of which model sits underneath. A platform with strong connectors and a slightly older model will deliver more practical value than a platform running the newest model in a closed box.

What to evaluate when choosing

If you are selecting an AI platform for your team, here is a practical framework.

What can it connect to? List the tools your business runs on. Email, CRM, project management, file storage, accounting. Check which AI platforms integrate with them natively. If the AI cannot reach your tools, it stays a chatbot.

What can it do without you? Look for agentic capabilities. Can the AI complete multi-step tasks, use tools, and check its own work? This is where workspace agents and computer use matter. The less you need to prompt step by step, the more time you get back.

Where does it sit in your existing workflow? The best AI platform is the one your team already uses. If your business runs on Microsoft 365, Copilot sits inside your existing tools. If your team uses Google Workspace, Gemini is already there. If you are platform-flexible, Claude and ChatGPT both offer strong standalone environments with growing integrations.

Can your team actually use it? This is the 80/20 question. 80% of AI adoption is people and culture. 20% is technology. The most capable model in the world delivers nothing if your team does not know how to use it, does not trust it, or does not have permission to try.

Where gecco fits

gecco works with UK SMEs to build AI adoption that lasts. We focus on the platform decision alongside the people decision, because one without the other fails. Our SCALE framework moves teams from awareness through to independence, regardless of which model or platform you choose.

If you want a clear read on where your business stands, take the AI readiness assessment.

Sources: OpenAI blog (23 April 2026), CNBC, TechCrunch, Fortune, Axios, SiliconANGLE, ofox.ai