Last year, artificial intelligence (AI) garnered significant attention, leading to a surge in companies seeking R&D tax credits for their AI initiatives. However, the complex nature of AI, coupled with the intricate qualification criteria of the scheme, often leaves businesses uncertain about their projects’ eligibility for these credits.
Established areas of AI, such as generative AI and Natural Language Processing (NLP), have formed the foundation for numerous R&D projects meeting the criteria for R&D tax credits. Nevertheless, some companies utilising established AI applications find they do not qualify. The subsequent sections of this article will delve deeper into this aspect.
This context provides a prime opportunity to explore the cutting-edge AI technologies showcased in the recent ’50 Emerging Technologies’ report by Innovate UK. These technologies are pushing the limits of AI and promise to transform various industries. Moreover, engaging in work related to these innovative AI domains significantly increases the chances of qualifying for R&D tax credits.
With this in mind, our article aims to explore the current AI landscape and its emerging domains, highlighting their innovative aspects and offering guidance to navigate the complexities of claiming R&D tax credits for AI-related costs.
What is the ’50 Emerging Technologies’ report?
The Innovate UK 50 Emerging Technologies report, released on December 6, 2023, explores seven technological sectors poised to revolutionise our future. These cutting-edge technologies, selected for their disruptive potential, societal benefits, and economic growth prospects, aim to inspire businesses to embrace these innovations, unlocking commercial opportunities and fostering job creation and economic prosperity.
We will concentrate on the report’s AI, digital, and computing segments, exploring groundbreaking advancements such as AI emotion and expression recognition, Artificial General Intelligence (AGI), biologically inspired AI, and Brain-Machine Interfaces (BMI).
The AI landscape: An overview
As of 2023, AI technology is at a crucial juncture, marked by groundbreaking advancements and heightened business adoption. The previous year’s McKinsey Global Survey underscored a significant rise in generative AI (gen AI) use across industries, with one-third of respondents indicating their organisations’ use of gen AI in at least one business function.
A recent article in UKTN highlighted generative technologies like ChatGPT as catalysts for the current AI boom, shifting its role from a niche technological speciality to a core business strategy.
Recent advancements and trends
The evolution of AI in 2023 is characterised by the rapid adoption of gen AI, as noted in the McKinsey report, underscoring its transformative impact on business processes and decision-making. Additionally, insights from UKTN reveal a trend towards more practical, value-driven applications of AI in business. This shift is evident in the growing focus on creating hyper-personalised experiences for end-users, leveraging historical data and user preferences.
The increasing role of AI
AI’s integration is expanding across diverse industries, as highlighted in the McKinsey report and UKTN. In healthcare, AI is revolutionising diagnostics and patient care. In finance, it is instrumental for risk assessment and fraud detection. Retail and manufacturing sectors are leveraging AI for personalisation and predictive maintenance. These developments highlight AI’s increasingly pivotal role in driving innovation and efficiency across various sectors.
Implications for R&D tax credits
The evolving AI landscape, especially with advancements in gen AI, presents promising opportunities for businesses to claim R&D tax credits. However, investing in innovative AI applications comes with unique challenges and advantages. To be eligible for R&D tax credits in AI, businesses must demonstrate how their AI projects address specific technological challenges or uncertainties. As AI expands its role across various industries, companies can explore new areas of AI that may qualify for these tax incentives.
However, the potential for businesses extends beyond just gen AI and NLP. The Innovate UK report highlights a diverse range of emerging AI technologies with the potential to shape the future of technology and innovation. While there are ample opportunities for innovation within gen AI and NLP, exploring other critical areas of AI, such as AGI (Artificial General Intelligence) and BMI (Brain-Machine Interface), is crucial.
These areas represent a shift towards more adaptive, human-like, and integrative approaches in AI technology. By delving into these technologies, we can understand their differences from mainstream AI applications and their potential to drive significant technological advancements.
Emerging technologies in AI
In AI, many emerging technologies are reshaping the limits of what can be achieved, going beyond the capabilities of generative AI (gen AI) and Natural Language Processing (NLP). As the Innovate UK report highlights, these cutting-edge technologies offer captivating new avenues for AI advancement.
AI Emotion and Expression Recognition
- Nature of technology: AI emotion and expression recognition, distinct from generative AI and NLP, focuses on understanding and responding to human emotions. This technology analyses facial expressions, voice tones, and body language to interpret human emotions effectively.
- Technological advancements: It has the potential to transform human-computer interaction, ushering in a new era of intuitive and empathetic experiences. Its applications range from enhancing customer service to providing support in healthcare settings, unlocking new possibilities for human-machine collaboration.
Artificial General Intelligence (AGI)
- Nature of technology: AGI marks a significant advancement beyond generative AI and NLP. Unlike current AI systems, which excel in specific tasks, AGI aims for a broad, adaptable intelligence akin to human intelligence. It can learn and perform a wide range of functions.
- Technological progress: AGI could lead to machines that are not merely tools but true collaborators. These machines possess creativity and the capability for autonomous decision-making, potentially transforming our approach to problem-solving and innovation.
Biologically Inspired AI
- Nature of technology: This AI form diverges from the data-driven approach of generative AI and NLP, drawing inspiration from the natural world, including evolutionary processes, neural networks, and swarm intelligence.
- Technological advancements: Biologically inspired AI could drive the development of adaptive and efficient AI systems, emulating the resilience and versatility found in biological organisms. It opens up new possibilities for AI that can evolve and adapt over time, leading to more sustainable and robust AI solutions.
Brain-Machine Interfaces (BMI)
- Nature of technology: BMI technology stands apart from generative AI and NLP by interfacing directly with the human brain, translating brain activity into commands for external devices, and vice versa.
- Technological advancements: BMIs hold immense potential, especially in healthcare and assistive technologies. They promise to restore or enhance human capabilities, providing hope for individuals with disabilities. Beyond medical applications, BMIs could redefine human-computer interaction, making it more seamless and intuitive.
R&D tax credits: Understanding eligibility and claims
R&D tax credits in the AI sector are a crucial incentive for innovation, particularly in advanced areas like generative AI and emerging technologies such as AGI, AI emotion and expression recognition, biologically inspired AI, and BMIs. These fields offer unique opportunities for businesses to leverage these credits effectively.
Aligning AI innovation with R&D tax credit eligibility
- Innovative AI projects: The cutting-edge technologies in the Innovate UK report epitomise the innovation that R&D tax credits are designed to encourage. These areas offer fresh opportunities for significant development, from pioneering work in AI emotion and expression recognition to groundbreaking advancements in AGI and BMI.
- Navigating technological uncertainties: Eligibility for R&D tax credits depends on demonstrating a project’s ability to resolve technological uncertainties. This is particularly relevant in emerging AI fields, where solutions and methodologies are still being defined. Developing AI systems capable of human-like learning or interpreting complex human emotions are examples of areas filled with scientific and technological uncertainties.
- Role of competent professionals: A critical factor in the credibility of an R&D project is the involvement of competent professionals, individuals with high-level qualifications, extensive experience, or recognised contributions in the AI field. Their expertise is crucial in defining technological baselines and advances and navigating the uncertainties inherent in innovative AI projects.
Challenges and misunderstandings
- Broad scope of eligibility: Contrary to common belief, R&D tax credits are not confined to completely novel inventions. Significant improvements or adaptations in AI technologies, both established and emerging, can qualify if they address specific technological challenges. This is where it can often get confusing, which is why it’s important to get the help of an R&D tax specialist to qualify and assess your project.
- Documentation of R&D activities: Accurate and comprehensive research process documentation is essential. This includes detailing the experiments conducted, the challenges faced, and the methodologies used in overcoming these challenges.
Practical tips for maximising R&D tax credit claims
- Early engagement with tax experts: Collaborating with R&D tax credit specialists from the outset can ensure that your project aligns with the criteria for these credits.
- Interdisciplinary collaboration: Effective communication between your technical and finance teams is vital for cohesive documentation and a comprehensive understanding of the R&D process.
- Adaptability and continuous learning: Staying informed about the latest AI developments and changes in tax legislation is critical to identifying new areas of innovation and understanding their impact on R&D tax credits.
The AI innovation landscape is undergoing rapid evolution. Exciting fields such as generative AI, AGI, AI emotion and expression recognition, biologically inspired AI, and BMIs offer groundbreaking business opportunities. The R&D tax credit scheme plays a crucial role in fostering innovation, serving as a significant incentive for companies venturing into these technologically uncertain domains. At EmpowerRD, we specialize in R&D tax credits, having successfully guided over 1,200 companies to claim more than £200m in credits. If you work in AI and are unsure about the eligibility of your project, we are here to provide comprehensive support. Should you have any questions or concerns, please feel free to get in touch with us.