What will technology look like in 2050?  

In this article, we cover: 

• What are AI agents and how will they change the future of work? 
• How are AI agents working with other AI agents? 
• Robotics operating alongside humans 
• World models helping AI understand the physical world
• How will AI affect creativity? 
• Quantum computing redefining what is computationally possible 
• Thought-controlled technology changing how we interact with machines 
• Post-quantum cryptography reshaping how organisations protect data

For centuries, humans have been predicting the future. Ada Lovelace dreamed of machines that could do more than add up; Alan Turing wondered if machines could even think; the internet was going to revolutionise the way billions of people communicated, worked and accessed information. One by one, the extraordinary things of the past slowly became part of ordinary life.

Today this is happening again: AI is no longer just a futuristic idea confined to research labs or science-fiction films, but is already here, writing emails, producing images, analysing data, writing code, and increasingly making decisions on our behalf. 88% of organisations now report regular use of AI, delivering productivity gains through automation and faster software development.

Looking towards 2050, AI systems may increasingly learn to complete more and more tasks without constant human supervision. AI systems may communicate and negotiate with other AI systems, and robots may enter physical environments to work side by side with humans.

It’s hard to predict what will happen, but developments underway today hint at what the future might bring.

What are AI agents and how will they change the future of work?

An AI agent is a software‑based system designed to perform specific tasks on behalf of a user or organisation. It can operate independently or collaboratively, utilising data, rules, and machine learning models to determine the actions to take.

AI agents are taking this concept to the next level by allowing people to delegate longer, more complex tasks rather than asking for answers one question at a time.

Research shows that 51% of organisations use agents in production today but this raises the question: who is responsible when an AI agent acts on your behalf? While an agent can decide and act, the responsibility ultimately lies with a human being or an organisation.

As technology becomes increasingly self-reliant, accountability becomes less easily addressed. The more autonomy we give these systems, the more important the questions of transparency, governance and accountability become. And as AI and automation take over more routine technical and administrative tasks, the skills that will become increasingly valuable are:

• critical thinking
• creativity
• communication
• flexibility
• adaptability
• problem-solving

How will AI agents work with other AI agents

The next stage of development could see AI agents increasingly working with one another. Instead of a person directing every step, different AI agents could communicate, delegate tasks and coordinate their actions to achieve a shared goal. One agent might analyse information, another could plan the next steps, while a third could carry out an action or check the results. For example, Microsoft’s AutoGen documentation shows a multi-agent coding workflow involving:

• Coder Agent — generates the code
• Executor Agent — runs the code
• Reviewer Agent — evaluates the results
• The reviewer can send feedback back to the coder for another round

This could create what is known as a multi-agent system, in which multiple specialised AI agents work together rather than relying on a single system to complete an entire workflow. For businesses, this could mean AI systems handling complex processes end-to-end, with individual agents taking responsibility for various parts of the task.

Robotics could operate alongside humans

The evolution of AI will not be limited to software. Advances in robotics, computer vision, sensors and autonomous systems could allow machines to increasingly operate in physical environments alongside humans.

This future is already taking shape. 542,000 industrial robots were installed globally in 2024, more than twice the number installed a decade earlier. There were also 4.66 million industrial robots in operational use worldwide at the end of 2024.

Robots could perform highly repetitive tasks, work alongside employees in factories, operate in warehouses and logistics networks, assist healthcare workers and potentially take on more responsibilities in homes. Autonomous vehicles and delivery systems could also change how people and goods move.

This could create a new form of human-machine collaboration. Employees could work alongside intelligent machines that can recognise their surroundings, make decisions and respond to changing environments.

World models could help AI understand the physical world

Another emerging development is the evolution of world models, a type of AI designed to understand and predict how the physical world behaves rather than simply describing it.

By learning from multiple sources, such as video, sensors and text, world models can create representations of real-world environments and potentially simulate what could happen before an action is taken. This could allow AI systems to become more flexible when operating in unfamiliar situations.

The implications could extend beyond AI software. World models could support robotics, autonomous vehicles, manufacturing and other technologies that need to understand and respond to physical environments.

How will AI affect creativity?

AI systems can already generate images, music, text, and videos within a few seconds.  This does not mean that generative AI will replace artists, graphic and text creators, but it will become another creative partner. A graphic designer can utilise an AI system to generate hundreds of design ideas, that they can further develop.

Deepfake technologies are synthetic media, video, audio, or images created and manipulated using artificial intelligence to appear authentic.

In the context of fraud, deepfakes are weaponised tools of deception. Common scenarios include CEO fraud, vendor impersonation, voice-based authentication bypass, and fabricated investment endorsements.

Quantum computing could redefine what is computationally possible

AI will not be the only technology transforming computing. Quantum computing could eventually allow organisations to tackle most problems that are too complex for conventional computers to solve efficiently.

One of the biggest concerns surrounding quantum computing is the potential arrival of “Q-Day” – the point at which a sufficiently capable quantum computer could break some of the public-key cryptography that currently protects digital communications and data.

The implications could extend well beyond cybersecurity. Quantum computing could have applications in areas such as drug discovery, financial modelling and risk, logistics and optimisation, materials science, climate modelling and scientific research.

The development of quantum computing therefore presents a dual challenge for organisations: preparing to take advantage of new computational capabilities while also preparing for the potential security risks that quantum technology could create.

Thought-controlled technology could change how humans interact with machines

The way people interact with technology could also change significantly. Rather than relying exclusively on keyboards, screens, touch interfaces or voice commands, brain-computer interfaces could eventually allow people to control digital systems through neural signals.

Potential applications could include controlling software or devices through thought, supporting people with disabilities, enabling communication without speaking or typing, controlling robotics or machinery remotely, and potentially creating new ways for people to interact with AI systems.

For example, Neuralink is developing an implant that allows people with paralysis to control computers and other devices using neural signals.  While these technologies are still developing, they point towards a future where the interface between people and technology becomes increasingly direct. 

Preparing for post-quantom world

As organisations adopt more advanced technology, they will also need to think about how they protect the systems and data that underpin it.

Post-quantum cryptography, for example, protects information against attacks from both conventional and future quantum computers. Lattice-based cryptography is one approach that uses complex mathematical structures to create encryption designed to remain secure in a post-quantum environment.

This means the future of technology will not simply be about developing more powerful systems. Organisations will also need to anticipate the risks those systems create and build security into technological change from the beginning.

How could new technologies transform different industries? 

The impact of these technologies will not be felt equally across every organisation. Their potential becomes clearer when looking at how they could reshape specific industries.

Healthcare 

AI could support diagnosis, medical research and drug discovery, while robotics could assist with surgery, care and other physical tasks. Brain-computer interfaces could also create new possibilities for assistive technology and communication. The global medical neurotechnology sector is projected to exceed $6.2 billion by 2030, driven by accelerating advances in artificial intelligence.

The combination of these technologies could shift healthcare towards greater personalisation and automation, while increasing the importance of human judgement, empathy and patient relationships.

Retail 

AI is already changing how retailers operate, with research showing that AI in e-commerce will be valued at $17.1 billion by 2030. AI-powered chatbots are handling order tracking, inventory and customer service, freeing up human space for more complex tasks.

Banking and finance 

AI agents could manage routine financial processes and support employees with analysis, research and decision-making. Quantum computing could eventually have implications for complex financial modelling, optimisation and risk analysis.

For instance, a leading multinational bank with over 80,000 employees and global revenues exceeding US$80 billion needed to automate its manual, human-based document review and reconciliation. Simultaneously, they had to meet strict governance standards and regulatory requirements.

In response, FDM assigned five AI-trained Python Engineers to automate manual tasks within the securitisation process, accelerate AI adoption, and drive digital transformation across the business.

What will the relationship between humans and technology look like in 2050?  

It is unlikely that the relationship between humans and technology in 2050 will be characterised solely by machines displacing humans. Instead, the relationship may become considerably more intermingled. AI agents may execute increasingly complex tasks.

The World Economic Forum estimates that 170 million new roles will be created, but at the same time, 32% of companies are currently experiencing skills gaps or expect to have them in the next few years.

This suggests that the defining challenge of the AI era may not simply be whether technology replaces jobs, but whether people and organisations can adapt quickly enough as the skills required to perform those jobs change.

At FDM, our consultants achieve AI fluency through intensive training covering prompt engineering, ethical AI use, and practical tool deployment: Capabilities that didn’t exist in traditional education years ago.

Conclusion 

Automation has changed the nature of work for centuries. The Industrial Revolution changed manual labour; computers changed office work; the introduction of ATMs changed how banks handle routine transactions, forcing them to adapt to changing customer needs. The next automation wave could be much faster and more widespread than previous ones.

As technological systems develop further, the distinction between human and machine work will diminish, and developers will be able to describe what they want to create, ask an AI system for a first version, evaluate its output, identify what is missing, and guide it toward the desired outcome.

How FDM can support    

While headlines focus on AI capabilities, the real challenge is more fundamental. 80% of tech executives report having postponed or slowed down important AI projects specifically due to a lack of skilled talent.

Without aligning skill forecasts and AI adoption plans, companies risk stalled transformations. FDM Consultants integrate seamlessly into your teams and accelerate your timeline from pilot to production.

Contact us to learn how our AI-ready consultants can help your organisation’s AI transformation.