Hasta La Vista, Manual Processes: Key Technologies and Trends in the Intelligent Automation Market

As automation technology continues to advance at a rapid pace, businesses are exploring new ways to streamline their operations and increase efficiency. The popularity of ChatGPT and other AI language models, which are rapidly rising to fame for their ability to automate an array of business processes, is perhaps the most prominent illustration of this trend. With their sophisticated natural language processing and machine learning capabilities, advanced AI language models are able to automate tasks such as writing compelling marketing copy, analysing customer feedback and much more. This means that businesses can spend more time focusing on activities that require real human creativity and strategic thinking…

A quick scroll through LinkedIn reveals just how difficult it can sometimes be to distinguish between human-written and AI-generated content. Unsurprisingly, we couldn’t resist the temptation to jump on the bandwagon and ask ChatGPT to write our introductory paragraph for us. This enabled us to, as our AI language model friend so neatly articulated, “spend more time focusing on activities that require real human creativity and strategic thinking” – such as coming up with the spate of somewhat questionable robot puns and references littered throughout this article!

ChatGPT and other AI language models are just one example of many technologies that are helping businesses to streamline their processes and reduce the burden of repetitive tasks. In this article, we look at some of the key emerging automation technologies and trends and consider the opportunities they may present to investors.

RPA, IPA and AI – what do they mean and how do they impact businesses?

Figure 1: The Journey to Intelligent Automation

Robotic Process Automation (RPA)

C3PO, The Terminator and Optimus Prime. Popularised fictional depictions of robots have constructed both heroic and villainous narratives about the role of robots in society. Whilst the robots used to automate business processes may lack metal suits, German accents or the ability to transform into trucks, they are already forming a core part of many digital transformation strategies around the world.

Touted as “the fastest-growing segment in the enterprise software market” by Gartner in 2021¹, Robotic Process Automation (RPA) refers to the use of software-based robots (“bots”) that mimic human actions to accelerate business processes by automating repetitive tasks. As an instructive technology, software bots follow pre-defined sets of rules to process structured data and execute specified, logical tasks. This means that RPA is perfectly designed to automate predictable and recurring processes. According to Gartner, the global RPA software market has grown rapidly in recent years from c.$500m in 2017 to an estimated $2.9bn in 2022². Due to the broad range of both sector-specific and sector-agnostic tasks that RPA can automate, it has gained traction across nearly all industries.

Intelligent Process Automation (IPA)

Despite strong growth in the RPA market, leading software vendors and market commentators are already focusing on how RPA can be combined with other technologies to deliver more value to businesses. Intelligent Process Automation (IPA) or Intelligent Automation (IA) refers to the enrichment of RPA with other advanced technologies in order to tackle more complex business processes that require human-like intelligence.

When combined with language detection technologies such as Optical Character Recognition (OCR) and Natural Language Processing (NLP), for example, software bots are able to handle unstructured data and interpret the meaning and/or emotion of text. This allows them to take on a wider range of tasks and further reduces the need for human involvement. For example, OCR technology enables software bots to scan and recognise text and numbers on receipts to automatically prepopulate expense claims. Equally, NLP allows bots to excel as chatbots which can understand conversational data and solve, or direct customers to the best place to solve, their enquiries (e.g. chatbots used by retailers/e-commerce businesses to redirect enquiries to the correct department).

Applying cognitive technologies such as machine learning and artificial intelligence on top of this can deliver even more value for businesses. These technologies’ analytical, processing and learning capabilities allow software bots to evaluate, optimise and update the rules they follow. This means that, rather than just learning how to execute a task or process, software bots are able to continuously learn how to complete them more effectively over time. An IPA solution being used to process insurance claims and flag those which require additional, human intervention or review, for example, could analyse the outcomes of flagged claims over time to monitor its own performance and improve its ability to highlight the claims which are most likely to need additional attention.

Recent projects completed by Fairgrove have revealed a small portion of the processes that intelligent automation solutions are helping businesses to automate across a variety of sectors, such as:

• Accounting – automating document processing and accounts reconciliation
• Software Quality Assurance – generating testing environments and test cases; processing test results
• Insurance – assessing, validating and processing claims
• Cybersecurity – automating penetration testing and threat hunting
• Recruitment – sourcing candidates, screenings CVs and automatically matching applicants with jobs
• Finance – matching and processing purchase orders, invoices and receipts

Importantly, the augmentation of RPA software with adaptive and cognitive technologies is increasingly enabling businesses to automate more complex and higher-value processes from end-to-end. The deployment of RPA technology alone, without complementary software, largely restricts businesses to streamlining and automating isolated tasks and activities. The ability to streamline entire processes, rather than single activities, enhances the value automation can deliver to businesses. As a result, leading RPA vendors have recently made a number of acquisitions in attempts to build and offer a more comprehensive set of solutions, reducing the need for end customers to buy multiple solutions and combine them in-house. Automation Anywhere’s purchase of FortressIQ, an AI-powered process discovery and mining platform; UiPath’s recent purchases of NLP and AI integration platform companies Re:infer and Cloud Elements; and Kofax’s acquisition of Ephesoft, an industry-leading intelligent document processing company, all reflect this strategy and highlight the trade exit opportunities that exist for specialist intelligent automation technology providers³.

Artificial Intelligence (AI)

Figure 2: Number of Months Taken to Reach 100 Million Global Monthly Active Users

Artificial intelligence, a term which refers to the ability of machines or computer systems to complete tasks that would normally require human intelligence to accomplish (e.g. learning, reasoning, problem-solving, perception, natural language understanding, and decision-making), has long been penned as a technological leap which could redefine how businesses, and the world, operate. ChatGPT’s rapid adoption (surpassing 100 million monthly active users in only two months⁴) makes it the fastest-growing consumer technology application of all time, gaining new users at a rate which can only be paralleled by the uptake of video conferencing software, Zoom, in the months following the onset of the COVID-19 pandemic in 2020.

Its success is emblematic of the widespread interest garnered by artificial intelligence’s possibilities. This interest is not immaterial. Investor interest in generative AI has grown rapidly in recent years, with global equity funding increasing from $71m across 23 deals in 2017 to nearly $2.7bn across 110 deals in 2022⁵. An investment by Microsoft (reported to be worth $10bn⁶) into OpenAI, the organisation behind the development of ChatGPT, will only accelerate funding in the space.

This investment and the ensuing development, release and adoption of AI solutions will generate further opportunities for investors as a host of training, configuration, consulting and other services are required to deploy these solutions and optimise their use for businesses around the world. To discover more about AI adoption in the area of Human Capital Management software, you can read Fairgrove’s recent thought leadership article here.

The automation ecosystem: don’t ignore the services market!

Figure 3: The Intelligent Automation Ecosystem

It is easy to focus on the rapidly growing automation software market, but the automation services industry is equally, if not more, exciting. Research conducted by Fairgrove suggests that the automation services market could be up to 7 times larger than the software market. Although leading software vendors offer some services to end-customers, this is not their forte, and they typically leverage vast partner networks to design, implement and optimise automation solutions. This has created space for a host of large-scale professional services firms and smaller pureplay automation specialists to enter the market and deliver important services across the value chain.

Figure 4: The Intelligent Automation Value Chain

Whilst the majority of businesses rely heavily on third parties to help them formulate, execute and optimise their automation strategies, some of the earliest-adopting and largest end-customers have developed in-house capabilities. Whilst insourcing may present a risk to the services market, there are a number of drivers helping to offset this risk and deliver further growth to the services market:

1. Many of the projects currently being delivered in-house have neatly defined use cases and involve the automation of individual tasks and activities. As automation solutions become increasingly intelligent and are used to automate end-to-end processes extending across business departments and involving a range of steps, tools and platforms, it is becoming more difficult to deliver these projects in-house and thus greater support from external experts is required.
2. Whilst large businesses are attempting to develop intelligent automation expertise internally, a lack of available talent is slowing progress. A pervasive skills shortage means that the hunt for talent is highly competitive and expensive. As a result, businesses are having to outsource projects to external specialists who have years of expertise and the required skillsets to deliver.
3. Rather than looking to improve their own service offerings, software vendors appear to be doubling down on, and strengthening, their partner networks, which is seen as a key route to winning new customers. Partners act as both the vehicle enabling the implementation and optimisation of solutions and the primary sales channel which funnels most new business to software vendors. As a result, software vendors are aligning themselves with partners and are actively investing in their growth. UiPath, for example, invested $20m across its Venture Innovation Fund and Partner Acceleration Fund to fuel growth across its partner network.
4. Increasingly affordable and accessible automation solutions (e.g., Robots-as-a-Service) are broadening the field of addressable companies, meaning that a growing number of SMEs and other non-traditional organisations are embarking on digital transformation journeys and implementing intelligent automation solutions. As a result, even if the largest and most mature companies develop in-house capabilities, the pool of companies requiring third-party support is likely to continue growing.

The expected future growth in the intelligent automation software and services market has attracted interest from both private equity and trade investors. Some recent investments and acquisitions are listed below⁷:

Figure 5: Recent Automation Services Acquisitions

Target	Acquirer	Date
Robiquity	Growth Capital Partners	July 2022
Himes Consulting Group	RubinBrown	July 2022
Extra Technology	BP3 Global	July 2022
BP3 Global	Horizon Capital	November 2021
Agilify	BP3 Global	August 2021
Step One Step Ahead	QA Mentor	November 2020
Roboyo	MML	September 2020
Symphony	Sykes	October 2018
Digital Workforce	CapMan Growth Equity Fund & Others	September 2018

Amidst macroeconomic instability, how recession resilient is the intelligent automation market?

Whether to help fight the Sith or the Decepticons, robots have often been called upon during times of crisis for assistance. Proponents of the idea that recessions provide a window of opportunity for businesses to invest in technology would argue that, despite increased uncertainty and tightening budgets, many businesses may look to invest in RPA and other intelligent automation solutions in the upcoming months as a means of streamlining processes and reducing costs. This notion presupposes the idea that businesses have the capital available to invest in intelligent automation solutions which can be incredibly expensive and require large up-front commitments to create, install and deploy bots. Past experience tells us that in a recession, projects which are funded and have already started typically continue as planned, whereas those which are yet to begin can be delayed and shifted right until the economy begins to recover and spare funds become available.

To overcome this and make automation solutions more affordable and accessible, Automation-as-a-Service (AaaS) delivery models are becoming increasingly popular. Boutique RPA consultancies Roboyo and Digital Workforce, for example, have developed Robots-as-a-Service (RaaS) offerings to provide customers with access to fully managed and maintained software bots on a subscription basis. In its 2022 Global Intelligent Automation Survey, Deloitte estimated that 17% of organisations are already implementing AaaS as a part of their intelligent automation strategies, with one-third planning to implement it over the course of the next three years. In the face of a recession and high levels of cost-push inflation, these figures are likely to see an uptick, meaning that vendors capable of delivering AaaS may prove to be the most resilient.

Figure 6: Customer Benefits of AI

In times of economic uncertainty, it can be easy to focus on the efficiency gains and cost-saving potential of automating time-consuming and repetitive business processes. Insight from the 2021 Deloitte Global Intelligent Automation Survey, however, suggests that businesses are also looking to leverage intelligent automation for more than just cost-cutting. Four of the top five target benefits were business-enhancing (and cash-generating) rather than cost-focused, with attempts to improve products, services, relationships and decision-making closely following ambitions to make processes more efficient. While reducing costs might be front and centre for many businesses in the short term, companies which are able to deploy automation to enhance product and service offerings, and improve decision-making will be prepared to face the unknown future with a sense of hope, and not be left behind (in a galaxy far, far away!).

Our Experience

If you would like to discuss this article or are considering investing in the automation market or any other areas Fairgrove has experience in, please contact Paddy Woods Ballard or Bhavna Dewan.

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Footnotes and Sources

¹ Gartner: Market Share Analysis: Robotic Process Automation, Worldwide, 2020, May 2021

² Gartner: Gartner Says Worldwide RPA Software Spending to Reach $2.9 Billion in 2022, Aug 2022

³ Sourced from company websites and press releases

⁴ According to a UBS report, Feb 2023

⁵ CBS Insights: The state of generative AI in 7 charts, Jan 2023

⁶ Forbes: Microsoft Confirms Its $10 Billion Investment Into ChatGPT, Changing How Microsoft Competes With Google, Apple And Other Tech Giants, Jan 2023

⁷ Sourced from company websites and press releases

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