2026 Technology Predictions

Each year IEEE Spectrum publish their technology predictions for the year. You don’t have to be an IEEE member but you do need to register to freely access the content. If you aren’t familiar with IEEE it is the Institute of Electrical and Electronics Engineers and the largest professional society in the world. I’m now a IEEE Senior Life Member and have appreciated theie support as an electronics engineer and business manager over the years starting when I was at Deakin University.

IEEE – Advancing Technology for Humanity

What are the 2026 technology predictions?

So here is the list:

• Grid-Scale Bubble Batteries
• Can Sound Waves Replace Scalpels in Cancer Treatment?
• Next-Level Quantum Computers Will Almost Be Useful
• Drones Tackle Wildfires in XPrize Competition
• Mesh Networks Finally Achieve Interoperability
• Will AI Replace Entry-Level Tech Jobs?
• Can Joby’s Air Taxis Beat Traffic in Dubai?
• Radio Cables to Boost Data Center Efficiency
• New Device Could Keep Weight Off After GLP-1 Drugs
• Porsche Debuts Inductive Charging for Cayenne EV
• Brain Chips and Foldable iPhones

The ones most likely to affect my business and the world as I view it are:

• Grid-Scale Bubble Batteries
• Can Sound Waves Replace Scalpels in Cancer Treatment?
• Mesh Networks Finally Achieve Interoperability

Grid Scale Bubble Batteries

The reasoning behind this selection is that this improves renewable energy reliability with cheaper and faster to build dispatchable storage; cancer treatment with less tissue destruction and commercial / consumer building / home automation with cross vendor integration so things can finally talk to each other and function together as a system.

The other one is Will AI Replace Entry-Level Tech Jobs?

My answer is ultimately “No”. But there will be short term losses when businesses mistakenly believe AI can replace most of their workforce. They will be wrong. And that will go through the usual correction. The statement I do believe is correct is that while AI won’t ultimately take my tech job away from me, someone who is good at using AI could. So I had better become good at using AI. As I see it, the things to consider are:

• Where can AI add efficiency and effectiveness to my job?
• How can I reduce the volume of output material down to a human digestible amount?
• How will I confirm that the AI generated output is correct?

The last one is a whole topic in its own right. And we have to understand Large Language Models are just one implementation option for AI. But if half the data a Large Language Model is trained on is wrong or not correctly classified, then half the answers are wrong.

Top tip for ChatGPT users: ask it to only give answers it has high confidence are correct. If you don’t do this, it will always provide an answer, even if it is demonstrably wrong.

The big issue with AI use in Software Development is that if a developer doesn’t fully understand the problem, then the solution can’t be everything you need it to be. So while we are using it in our operations, AI is not replacing my people anytime soon. And tools that can generate too much output for a person to be competently across are actually more of a problem than a help.

You can check out all the predictions at IEEE Top Tech 2026.

Successful Endeavours specialise in Electronics Design, Embedded Software Development and Electronics Manufacturing, focusing on products that are intended to be profitably Made In Australia. Ray Keefe has developed market leading electronics products in Australia for more than 40 years.

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