What is Artificial Intelligence?

Discover how AI is redefining the way we work.

+ Types of AI: Generative AI has transformed the workplace.
+ Barriers to greater AI adoption: What is holding back companies from implementing AI more widely?
+ AI in the workplace: Benefits for SMEs of adopting AI to harness its potential fully.
Graphic of AI-created robot holding a laptop
Graphic showing AI chip and a network

Artificial intelligence definition

What is AI? Artificial Intelligence feels like a new concept, but actually it is generally believed to date from 1955 when a young maths assistant professor in the US called John McCarthy suggested that:

"every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."

He called this emerging field of study "artificial intelligence"

Even before that, Alan Turing, in his work "Computing Machinery and Intelligence", published in 1950, asked the question, "Can machines think?" 

Over 70 years later, artificial intelligence has made enormous strides, and one of the leading players responsible for driving much of the progress, Google, has used its vast knowledge and experience to define AI as the following:

Understanding the Basics of Artificial Intelligence

AI development can be broadly categorised into four progressive stages, each offering unique capabilities to transform and enhance the way businesses operate.

Reactive Machines: These early AI systems operate based on preprogrammed rules, lacking memory and learning capabilities. Their primary function is to react to stimuli, excelling in simple classification and pattern recognition tasks. IBM's Deep Blue, the chess-playing computer that defeated Garry Kasparov in 1997, exemplifies a reactive machine.

Limited Memory AI: The majority of today's AI falls under this category, characterised by artificial neural networks that learn and improve using stored data. These machines leverage deep learning, a subset of machine learning, to handle complex tasks such as autonomous driving. However, limited memory AI requires vast amounts of training data and is vulnerable to outliers or adversarial examples.

Theory of Mind AI: A future development in AI research, Theory of Mind AI seeks to emulate human decision-making and emotional intelligence. This Artificial General Intelligence (AGI) aims to understand human motives and reasoning, allowing for personalised results and adaptability to a wide range of problems. While artificial emotional intelligence is being developed, current systems are far from self-awareness.

Self-Aware AI: The ultimate frontier in AI development, self-aware AI envisions machines that possess self-awareness and intellectual capabilities on par with or surpassing human cognition. Also known as Artificial Superintelligence (ASI), this AI would continuously create more intelligent versions of itself. However, our current understanding of the human brain is insufficient to create such advanced AI systems.

UK Artificial Intelligence Sector


UK AI Companies


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AI related revenues


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Registered AI Companies by Size

The AI sector has a greater concentration of large, medium and small businesses than the general UK Business population.
Micro (1-9 employees)60%
Small (10-49 employees)28%
Medium (50-249 employees)8%
Large (250+ employees)4%

Different types of Artificial Intelligence




Artificial Intelligence (AI) can be classified into three main types: narrow, general, and super.

Narrow AI excels at specific tasks, like virtual assistants and recommendation systems.

General AI, a theoretical concept, envisions machines with human-like intelligence capable of handling various tasks.

Super AI, a hypothetical future development, represents machines surpassing human intelligence, potentially revolutionising technology and society.

Each type of AI presents unique possibilities and challenges, shaping our future landscape.

Generative AI is expected to achieve:

~30% of overall AI market share by 2025

~$60bn of the total addressable market

Source: BCG analysis

Weak AI - Narrow AI or Artificial Narrow Intelligence (ANI)

Artificial Narrow Intelligence (ANI), often referred to as Weak AI, is the driving force behind today's AI applications in business. While it may not possess the broad cognitive abilities associated with human-like intelligence, ANI excels in performing specific tasks or solving particular problems, making it an indispensable tool for enhancing efficiency and innovation in the modern workplace.

From voice assistants like Siri, Alexa, and Google Assistant to powerful algorithms in image recognition and customer service, including chatGPT, ANI showcases the remarkable potential of AI in a wide array of applications. Though it operates within a narrow scope, ANI can deliver transformative results, revolutionising how we work and live on a global scale.

According to McKinsey, "About 75 percent of the value that generative AI use cases could deliver falls across four areas: Customer operations, marketing and sales, software engineering, and R&D"

Despite being labelled as "weak" AI, ANI's capabilities are driven by sophisticated algorithms and neural networking, making it a potent force in the business world as its capacity for driving efficiency and optimisation should not be underestimated.

General AI - Strong AI or Artificial General Intelligence (AGI)

Artificial General Intelligence (AGI), often referred to as "strong AI," represents the ultimate goal in AI research – a machine with the ability to emulate human intelligence, think abstractly, strategically, and creatively, while handling a wide array of complex tasks. Currently a theoretical concept, AGI promises a future where machines possess common sense and consciousness, transcending the limitations of today's narrow AI systems.

Imagine a world where AGI systems can learn from experience, detect patterns, and extrapolate that knowledge across a multitude of tasks and situations, unbound by previously acquired data or existing algorithms. This revolutionary leap in artificial intelligence would significantly transform businesses by providing an unprecedented level of cognitive power, driving innovation and efficiency beyond our current capabilities.

Though the realisation of AGI remains a distant prospect, glimpses of its potential can be seen in projects like the Summit Supercomputer, which can perform an astonishing 200 quadrillion computations per second – a feat that would take a human billions of years to achieve. To harness the full potential of AGI for businesses, we must continue to push the boundaries of computational capacity and explore the possibilities of human-machine collaboration.

As we progress towards the realisation of AGI, businesses must prepare for the groundbreaking opportunities it presents. Embracing the power of Artificial General Intelligence will redefine the business landscape and unlock unparalleled potential for growth, innovation, and success.

Super AI - Artificial Super Intelligence (ASI)

Artificial Super Intelligence (ASI) represents the zenith of machine intelligence, with the potential to not only revolutionise the business landscape but also redefine the very fabric of human society. While it may sound like a futuristic concept, ASI is a system where a machine's intelligence surpasses all human capabilities, outperforming us in every conceivable function.

Although still a hypothetical concept, an intelligent system that can learn and continuously improve itself could lead to extraordinary breakthroughs and advancements in various fields, such as medicine, technology, and beyond. ASI systems are theorised to be fully self-aware, grasping human behaviour at a fundamental level and exhibiting human traits combined with unparalleled processing and analytical power.

While ASI may evoke visions of a dystopian, sci-fi future where humans become increasingly obsolete, it's crucial to consider the ethical guidelines and responsible stewardship in anticipation of artificial intelligence that could outstrip us in every measurable way. The advent of ASI may not be imminent, but its potential to reshape businesses and unlock boundless opportunities makes it a compelling force for future innovation and growth.

Four distinct technologies or subfields of AI

man analysing machine learning algorithms graphic

Machine Learning

Machine Learning is a branch of Artificial Intelligence that enables computers to learn and improve upon tasks without being explicitly programmed to do so. By using statistical techniques, Machine Learning algorithms identify patterns in big data and use these patterns to make predictions or decisions. These algorithms can be trained to identify patterns in a wide variety of data, including text, images, and speech.

Machine Learning has many practical applications in the business world, such as in fraud detection, customer segmentation, and product recommendations.
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Natural Language Processing

Natural Language Processing is a subfield of Artificial Intelligence that deals with the interaction between computers and human language. NLP involves teaching machines to understand, interpret, and generate human language. This technology is used in applications such as chatbots, voice assistants, and language translation tools.

NLP is particularly important for businesses that deal with a large volume of customer inquiries or that need to provide multilingual customer support.
man and woman talking via computers analysing data graphic

Computer Vision

Computer Vision is a field of Artificial Intelligence that enables computers to interpret and understand visual information from the world. It involves developing algorithms that can analyse, identify, and classify objects in images or videos. Computer Vision has many practical applications in the business world, such as in quality control, object detection, and facial recognition.

For example, Computer Vision can be used to monitor production lines and identify defective products, or to track customer behaviour in retail stores and provide targeted marketing messages.
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Robotics is the application of Artificial Intelligence to the field of robotics, which involves the design, construction, and operation of robots. AI is used to create intelligent robots that can perform complex tasks, such as navigation, manipulation, and decision-making.

Robotics has many practical applications in the business world, such as in manufacturing, logistics, and healthcare. For example, Robotics can be used in a factory to assemble products, in a warehouse to pick and pack orders, or in a hospital to assist with surgeries.

Barriers to greater AI adoption within industry

To maintain the UK's leadership in AI and realise its goal of becoming a global powerhouse, it is essential to comprehend the obstacles hindering wider AI adoption in the industry and devise strategies to overcome them amidst this period of unparalleled transformation and expansion.

techUK’s AI Adoption Working Group has pinpointed five principal themes that may impede the more extensive deployment of AI in the industry.

1. Inconsistent data quality & accessibility
2. Lack of trust in AI
3. A limiting organisational culture & understanding of AI
4. Insufficient compute infrastructure
5. Gap in AI skills

Within large organisations, 90% have already implemented AI, or have actively planned for its adoption. For SMEs, this figure was 48%.

Read more about techUK's recommendations to ensure that the UK build on its very strong position in AI to unlock the full range of opportunities that AI presents.

Artificial Intelligence in the Workplace

Benefits of incorporating AI into your business

Harnessing the power of Artificial Intelligence (AI) in the workplace can revolutionise businesses by streamlining operations, enhancing decision-making, and elevating customer experiences. By adopting AI, organisations can reap numerous benefits, including:

Automating repetitive tasks: AI can efficiently manage time-consuming, routine tasks such as data entry, customer support, and scheduling. By automating these processes, such as AI chatbots, employees can focus their efforts on more strategic, higher-value work, ultimately boosting productivity and job satisfaction. McKinsey think that "Current generative AI and other technologies have the potential to automate work activities that absorb 60 to 70 percent of employees’ time today."

Enhancing decision-making: AI-powered tools can provide valuable insights by analysing large volumes of data. Predictive analytics, market trend analysis, and risk assessment are just a few examples of how AI can help businesses make more informed decisions, driving growth and reducing potential losses.

Improving customer experiences: AI technologies can elevate customer engagement and satisfaction by providing personalised interactions. Chatbots can handle customer queries 24/7, while personalised recommendations and sentiment analysis enable businesses to better understand their customers' preferences and emotions, fostering long-lasting relationships.

Adopting AI into your business

To successfully implement AI within your organisation and harness its potential, consider the following steps:

Identifying areas of improvement: Evaluate your business processes and pinpoint where AI can make the most significant impact, ultimately improving efficiency and effectiveness.

Selecting the right AI solution: Explore various AI technologies and choose the one that aligns with your business goals and needs. Generative Artificial Intelligence can be utilised in your business to create original content, designs, or solutions based on provided data. By harnessing its ability to generate unique outputs, you can enhance your creative processes, produce personalised marketing campaigns, and streamline your product development. Consult experts and research case studies to make an informed decision.

Integrating AI into existing systems: Seamlessly incorporate AI solutions into your current workflows and infrastructure, ensuring a smooth transition and minimal disruption to daily operations.

Utilise Data Science: This is a multidisciplinary field that enables your business to extract valuable insights from vast quantities of big data. By harnessing big data through advanced analytical techniques, your company can make informed decisions and drive innovation.

Training employees and fostering AI adoption: Educate your team on the benefits of AI and provide them with the necessary training to use AI tools effectively. Encourage a culture of curiosity and learning to maximise the potential of AI within your organisation.

When adopting AI, it's essential to be aware of potential challenges and risks, such as:

Data privacy and security: Ensure the protection of sensitive information by implementing robust security measures and adhering to data protection regulations.

Ethical considerations: Establish guidelines and policies that address ethical concerns surrounding AI, such as bias and transparency.

Managing employee concerns: Address potential fears and apprehensions about job displacement or skill requirements by promoting open communication, retraining, and upskilling opportunities.

By understanding and mitigating these challenges, businesses can unlock the full potential of AI, transforming their operations and driving sustainable growth.

A pro-innovation approach to AI regulation

"Public trust in AI will be undermined unless these risks, and wider concerns about the potential for bias and discrimination, are addressed. By building trust, we can accelerate the adoption of AI across the UK to maximise the economic and social benefits that the technology can deliver, while attracting investment and stimulating the creation of high-skilled AI jobs. In order to maintain the UK’s position as a global AI leader, we need to ensure that the public continues to see how the benefits of AI can outweigh the risks."

UK Government Policy Paper: 29 March 2023

Warnings about Artificial Intelligence and its potential impact

The adoption of AI brings several risks and concerns that need to be carefully addressed to ensure responsible and ethical implementation. Key areas of concern include:

Data privacy and security: As AI systems rely on large volumes of data to function effectively, there is an increased risk of data breaches and misuse of sensitive information. Ensuring robust data protection measures and compliance with regulations are crucial in mitigating these risks.

Bias and discrimination: AI algorithms can inadvertently perpetuate and exacerbate biases present in training data, leading to unfair and discriminatory outcomes. Ensuring diverse and representative data sets, along with regular audits of AI systems, is necessary to minimise bias.

Ethical considerations: AI raises various ethical questions, such as transparency, accountability, and fairness. Establishing guidelines and ethical frameworks to govern AI development and usage is essential to address these concerns.

Job displacement: AI automation can lead to job losses in certain sectors, causing workforce disruptions and social inequalities. Retraining and upskilling initiatives, along with creating new job opportunities in emerging industries, can help mitigate this issue.

Misaligned goals and unintended consequences: AI systems may develop unintended behaviours or optimise for the wrong objectives, resulting in undesired outcomes. Ensuring proper alignment of AI goals with human values and robust monitoring of AI behaviour can help address this concern.

Weaponisation of AI: AI advancements can be exploited for malicious purposes, such as autonomous weapons or surveillance systems, raising concerns about security and privacy. International cooperation and regulations are needed to prevent the misuse of AI technologies.

Concentration of power: The rapid development of AI technologies can result in an unequal distribution of power and resources, particularly among large corporations and governments. Promoting equitable access to AI benefits and resources can help counterbalance this concentration.

Artificial General Intelligence (AGI) and Superintelligence: The potential future development of AGI and Superintelligence poses concerns about the long-term implications for human society, such as the control and alignment problem. Collaborative research and ethical guidelines are essential to ensure the safe development of advanced AI systems.

Specific areas of concern regarding the use and application of AI

Several AI applications and technologies have raised concerns due to the risks they pose in various aspects. Some specific examples include:

Facial recognition technology: While this technology can improve security and streamline identification processes, it raises concerns about privacy, surveillance, and potential misuse by authoritarian governments or malicious actors. Additionally, biases in training data can lead to discriminatory outcomes.

Deepfakes: AI-generated videos or images that convincingly mimic real people can be misused to spread misinformation, manipulate public opinion, or harm reputations. The increasing accessibility and sophistication of deepfake technology pose significant challenges to discerning truth from falsehood.

AI-driven social media algorithms: While these algorithms help tailor content for users, they can also inadvertently amplify echo chambers, promote the spread of misinformation or extremist content, and contribute to mental health issues due to excessive use or social comparison.

Autonomous weapons: AI-enabled military systems, such as drones or robotic weaponry, raise ethical concerns about the delegation of life-and-death decisions to machines. These technologies can potentially be misused or lead to unintended consequences in conflict situations.

AI-driven hiring platforms: These platforms use AI algorithms to assess job applicants, but can perpetuate biases and discrimination if the training data or evaluation criteria are skewed. This can result in unfair hiring practices and exacerbate existing inequalities in the workforce.

AI-powered surveillance systems: While AI can enhance security and monitoring capabilities, its use in mass surveillance systems raises concerns about privacy invasion and potential misuse by governments or corporations to track and control individuals or groups.

AI chatbots and virtual assistants: These tools can improve customer experience, but also pose risks in terms of privacy, data misuse, and the propagation of biased or inappropriate content if not properly monitored and regulated.

By being aware of the risks associated with these AI applications, businesses and policymakers can work together to implement robust guidelines, regulations, and ethical frameworks to ensure the responsible and equitable use of AI technologies.

Workplace benefits of AI

Yoho Workplace Strategy: Survey of 600 UK-based HR managers and directors

Improvements in decision-making support

Productivity and efficiency

Automation of routine tasks

Increases in innovation and creativity

Which jobs will be most impacted by AI

Yoho Workplace Strategy: Survey of 600 UK-based HR managers and directors

IT and technology

Finance and Accounting

Customer Services and Support

Sales and Marketing

UK Government: National AI Strategy

10-year plan to make the UK an AI superpower

The UK National AI Strategy aims to prepare the nation for the next decade by capitalising on its existing strengths in AI and addressing future challenges.

The strategy focuses on investing in the AI ecosystem, transitioning to an AI-enabled economy, and establishing proper governance for AI technologies. It is built on three assumptions:

AI progress will depend on access to people, data, computing, and finance;

AI will become mainstream in the economy;

Governance and regulatory regimes will need to keep pace with AI advancements.

The 10-year vision seeks to position the UK as the best place to live and work with AI, ensuring the nation experiences significant growth in discoveries, and economic growth due to AI, and establishes the most trusted pro-innovation AI governance system in the world.

The strategy is supported by multiple interconnected government initiatives, including the Plan for Growth, the Integrated Review, and the National Data Strategy.

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