In just a few months, 2026 will not feel like “the future” any more.
Your calendar will quietly rearrange itself. Your energy bill will be optimised before you even know tariffs have changed. A digital assistant will nudge you about your cholesterol and remind you that you promised to call your mum.
That is the world painted by a new global study from IEEE, which surveyed 400 CIOs, CTOs and technology leaders across six major economies to understand how artificial intelligence and related technologies will reshape work and daily life in 2026 and beyond. [1] [2]
And the headline is clear: Agentic AI is about to move from experimental gadget to everyday companion.
Agentic AI: From clever tool to autonomous helper
IEEE focuses heavily on agentic AI in this research. Think of agentic AI as an assistant you can delegate tasks to. You tell it what outcome you want, it plans the steps, calls other tools and services, and reports back. It is not magic, and it still needs human oversight, but it acts with a degree of independence. [2]
Almost all of the leaders surveyed, a remarkable 96 percent, expect innovation and adoption around this kind of AI to keep accelerating at “lightning speed” in 2026. [1] [3]
Crucially, they do not see this as just a business phenomenon. They believe agentic AI will hit mass or near mass consumer adoption next year in very specific ways:
- Personal assistant, scheduler and family calendar manager
- Data privacy manager
- Health monitor
- Automating errands and chores like grocery orders
- Curating news and information
In each of these categories, large shares of respondents expect widespread consumer uptake in 2026, with personal assistants and schedulers topping the list. [2] [4]
If you have ever felt that digital assistants are a bit underwhelming today, the IEEE study suggests that is about to change drastically.
AI in the workplace: Co-worker, not science fiction prop
The study also looks at the workplace, and the picture is just as dramatic.
A strong majority of respondents say humanoid robots will initially be a novelty in offices and industrial settings, but will eventually become “commonplace coworkers with circuits”. [2] [5] Robotics is identified as the single biggest technology area that AI will influence in 2026, ahead of extended reality and autonomous vehicles. [1] [2]
Under the bonnet, the most widely expected uses of AI next year are not glamorous sci-fi scenarios but very practical ones:
- Real time cyber security threat detection and prevention
- Assisting and accelerating software development
- Increasing supply chain and warehouse efficiency
- Automating customer service
- Supporting education, disease mapping and even stabilising power grids
These use cases tell a simple story. AI is becoming a systems technology, quietly woven into infrastructure, logistics, support and operations rather than existing as a separate, shiny project on the side. [2] [6]
If you run an organisation, the implication is straightforward: Your competitors are not just “experimenting with AI”. They are embedding it into the nervous system of their business.
Jobs in 2026: Augmented, not annihilated
The IEEE study also challenges some of the more extreme narratives about AI taking all the jobs. These leaders expect a world where AI is almost everywhere, but very rarely completely in charge.
More than half of respondents think that in 2026 roughly a quarter to half of all jobs globally will be augmented by AI software. Far fewer believe that most jobs will be fully automated. [2]
That word “augmented” is key. It implies:
- Customer support agents working alongside AI that drafts responses and pulls up context.
- Engineers using AI copilots that generate code, test cases and documentation.
- Operations teams using AI to predict bottlenecks in logistics or production.
You are still in the loop. You are just no longer doing everything manually.
Interestingly, the study expects AI adoption inside organisations to mature rapidly next year. Many technology leaders see their companies moving from simple trials to using generative AI regularly, with a growing proportion saying it will be integrated across operations with measurable impact on the bottom line. [2] [7]
If the last few years were those of AI hype and experimentation, 2026 looks set to be the year of serious implementation.
The surprising skill that matters most: AI ethics
If AI is about to become a constant background presence, who will design, deploy and police it?
When IEEE asked leaders what skills they most want to see in AI related hires for 2026, the top answer was not “machine learning” or “software development”. It was AI ethical practices. [1]
Close behind were data analysis, machine learning, data modelling and software development. Taken together, this skills list tells us a lot about how AI is evolving:
Ethics is moving from an afterthought to a core competency.
Companies do not just want people who can build AI systems. They want people who can ask whether they should, and how they can do it safely and fairly.
Data is the real fuel
Data analysis and modelling rank as highly as traditional coding skills, reflecting the reality that the quality, governance and structure of your data often matter more than the cleverness of your algorithms.
AI is becoming a team sport
Interdisciplinary teams that combine technical, legal, compliance, user experience and domain expertise will be the ones who can turn AI into durable competitive advantage.
The IEEE study also notes that 91 percent of leaders expect the use of agentic AI to analyse ever larger volumes of data to grow in 2026, creating strong demand for data analysts who can validate results, check for bias and understand vulnerabilities. [8] [9]
In other words, as AI becomes more capable, the value of human judgement actually increases.
The coming infrastructure crunch
All of this intelligence has to live somewhere.
One of the most striking findings in the study is that almost half of respondents think it will take five to seven years to build out the global data centre capacity needed to meet demand for AI development and usage. A third believe it might happen within three to four years, while a smaller group think the world will be waiting longer. [1]
That is not just a technical detail. Data centres are heavy consumers of energy and water, and they sit at the crossroads of climate policy, national security and local planning. As AI workloads grow, so does the pressure on electrical grids and the importance of cleaner energy sources.
This infrastructure story becomes even more interesting when you remember that the wider Internet of Things ecosystem is exploding in parallel. By early 2026 the number of connected devices worldwide is expected to surpass 25 billion, on the way to roughly 40 billion by the end of the decade.
Every one of those devices is a potential source of data for AI systems and a potential consumer of AI driven decisions, whether that is a thermostat optimising heating or an industrial sensor predicting machine failure. If today’s internet was built for people, the next phase is being built for people and things and the AI systems that connect them.
Policy and governance: Who do you trust with your AI?
IEEE’s research also touches on how organisations think about AI built in house versus AI from third parties.
Many leaders say their company will move “full speed ahead” with AI that they have developed themselves, integrating it widely and aligning usage policies with whatever regulations exist. When it comes to AI built by external suppliers, fewer are quite so gung-ho and more emphasise clear internal rules and governance. [2] [10]
That split reveals an important trust question for the coming years:
- How much do you trust your own teams to build safe, compliant, transparent AI systems?
- How much do you trust vendors whose models you cannot fully inspect?
- How will regulators, auditors and customers react if you cannot explain the behaviour of a system that affects them?
As AI moves deeper into healthcare, finance, transport and energy, these questions stop being abstract. They become contract clauses, audit findings, front page headlines and real world consequences. The organisations that win will be the ones that treat AI governance as seriously as financial governance or cyber security, not as an optional extra.
What this means for you in 2026
Put all of these findings together and a clear picture emerges. By 2026:
- AI will be a normal part of both home and work life, especially in the form of agentic assistants that handle scheduling, chores, privacy and basic health monitoring. [2] [4]
- Many jobs will be reshaped rather than replaced, with AI embedded into workflows for security, software development, operations and customer experience. [2] [6]
- The most sought after skills will blend technical depth with ethical awareness and strong data literacy. [1] [5]
- Infrastructure, from data centres to energy grids to networks, will be under immense pressure to keep up. [1]
So what should you actually do? Here are some practical moves inspired by the study’s findings:
Start small, but start with real work
Pick one or two agentic AI use cases that genuinely reduce friction in your organisation: Perhaps an internal assistant that drafts documentation, or an AI powered support tool that helps staff answer complex queries. Tie them to measurable outcomes rather than running AI pilots in isolation.
Invest in your data foundations
Before you chase the next model, make sure your data is clean, well governed and accessible. The leaders in the IEEE study are telling you that data skills and modelling matter as much as pure model building. If your data is a mess, your AI will be, too.
Build an ethics and governance habit
Do not wait for regulators to force your hand. Start defining principles, checklists and approval processes for AI projects now. Give people with ethical and legal expertise a real voice in technical discussions, and reward teams for raising concerns early.
Develop your people, not just your tech stack
Encourage your teams to build AI literacy across the board. Teach non technical staff how to work effectively with AI tools, not just how to avoid them. Create pathways for data analysts, engineers and product owners to deepen their skills in AI, security and privacy.
Think long-term about infrastructure
If your organisation plans to rely heavily on AI, understand how that affects your energy usage, hosting strategy and resilience. Explore partnerships, cloud strategies and sustainability commitments that will still make sense when AI workloads double or triple.
The future is quietly arriving
What makes the IEEE study so striking is not the science fiction imagery. It is the normality of it all.
In this 2026, AI is everywhere and almost nowhere at the same time. It is behind the scenes in data centres and warehouses, embedded in robots and utility grids, and humming away on your phone as an ever more capable assistant. It is influencing huge strategic questions about jobs, skills and infrastructure, while also helping you remember dentist appointments and pick a better mobile tariff.
The key question is no longer “Will AI change things?” it’s “Who will be ready when it does?”
Whether you are a CIO planning your next transformation initiative, a developer thinking about your career in an AI saturated market, or simply someone wondering what your life will look like in a year’s time, the message from IEEE’s global snapshot is simple: The future is not waiting for us to feel prepared.
It’s already putting meetings in our calendars.
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