AI at Work in 2026: Productivity Boost or Hidden Risk? The Answer Is Skill

The year AI moved from answering to working

As 2026 draws to a close, the leading AI tools have gained a long list of new abilities. OpenAI introduced GPT-6 in ChatGPT in October, after adding scheduled recurring tasks mid-year. Anthropic released several upgrades to Claude, including Claude Opus 5 in July, built for long-running, complex work, and Claude Fable 5.2 in November, aimed at demanding technical tasks. At Google I/O in May, Google launched Gemini 3.5 Flash, described as a series “combining frontier intelligence with action”, along with Docs Live, which lets users create and edit documents by voice. Microsoft 365 Copilot now lets users call Word, Excel and PowerPoint agents directly from the chat, and has added Claude models alongside OpenAI’s.

The common thread: AI no longer just answers questions. It takes on tasks, works through several steps and returns finished output.

How daily work has changed

In the office, tasks that used to take hours now take minutes. A monthly report can be drafted from raw figures. Customer emails come out in the company’s tone. Meeting notes become summaries with action items and owners. Spreadsheets with thousands of rows are filtered, summarised and charted with one instruction. Project plans, training schedules and document registers are organised faster.

Oil and gas and industrial companies are seeing the same shift. Maintenance engineers use AI to compile shift logs, compare them with failure history and draft maintenance reports. HSE teams review safety documentation, standardise risk assessment templates and summarise incident reports. HR and training managers track training records, flag expiring certificates and plan the annual training programme. Technical teams draft operating procedures, review tender documents and summarise technical documents hundreds of pages long. These are weekly tasks for people in the industry, and AI is shortening each one.

When AI is used carelessly

AI is useful, but careless use causes real damage. Three causes come up again and again.

First, people don’t know how to instruct it. A vague request such as “write a safety procedure for work at height” produces a generic document that may look professional but does not match the site’s equipment, standards or conditions.

Second, AI gets wrong or incomplete input. AI can only work with what it is given. When data is missing, it may fill the gaps with figures that sound plausible but are not real. In 2023, a US federal court sanctioned lawyers who filed a brief citing court cases that ChatGPT had invented. In our industry, the equivalent is a report with wrong figures or a procedure with made-up steps.

Third, output isn’t checked and data isn’t protected. Also in 2023, Samsung restricted staff use of generative AI after engineers pasted internal source code into ChatGPT. Now picture technical documents, well data or tender files pasted into a public tool.

In an office, an AI error may cost time to fix. In a safety-critical industry, a wrong figure in a report or an invented step in a procedure can cost far more.

The solution: learn to assign work to AI

The gap between using AI and using it well is not about the tool. It is a skill, and it can be learned.

People who are properly trained assign work to AI the way they would brief a new colleague: they explain the context, the purpose, the audience and the format. They supply the right documents and data instead of letting AI guess. They break large tasks into steps, ask AI to show its sources, and, most importantly, check the result before using it. They also know which data may go into which tool under company policy.

You can pick these skills up by trial and error, but learning from an expert, or through a course that practises on your own work, is faster and safer.

AI won’t replace people who know how to use it

Many people worry that AI will take their jobs. No one can promise that every job will stay the same. But there is a more reasonable way to look at it: AI handles the repetitive parts (drafting, compiling, formatting), while professional judgement, sign-off responsibility and site knowledge stay with people.

Those who learn to work with AI get more done in the same time, spend more time on work that needs expertise, and become more valuable to their employers. The people most at risk are not those who use AI, but those who never learn to work with it.

Start with the right course

If you or your team already use AI but have never been trained, now is a good time to start. The Advanced AI – Copilot course at PVD Training, a training centre serving the oil and gas and industrial sectors, helps learners apply AI to their own daily work.