IA today: plotting a roadmap to success

November 2019  |  FEATURE  |  BOARDROOM INTELLIGENCE

Financier Worldwide Magazine

November 2019 Issue

Intelligent automation (IA) has become a driving factor toward delivering efficient and cost-effective business models in recent years – a roadmap to enable companies to gain greater value from data, systems and human resources.

The catch-all phrase for disruptive technologies, IA includes robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), cognitive computing (CC) and smart analytics. Moreover, the increasing appetite for IA is evidenced in a survey by the Artificial Intelligence & Intelligent Automation Network in which 71 percent of respondents stated that IA was their chosen mechanism for improving business productivity and efficiency.

Further evidence of the scope of IA is provided by KPMG in its 2019 ‘Easing the pressure points: The state of intelligent automation’ report, which, based on the views of nearly 600 business leaders, including 100 top-level executives across six industries and 13 countries, notes that more than 30 percent of businesses have already invested more than $50m in IA technologies.

“There are various numbers provided by analysts showing how fast the IA market is growing,” says Sascha Cutura, chief executive of the Convedo Group. “We are seeing an explosive growth in IA adoption as businesses want to automate mundane, repetitive tasks and enjoy fast return on investment. The quick adoption of IA is in turn driven by data growth. With businesses faced with the challenge of rising data management costs, IA offers an effective solution for scaling their data, without making massive investment.”

Constantly evolving, recent trends and developments impacting the IA space include the following observed by James Dening, vice president at Automation Anywhere. First, AI and ML have enabled IA to surpass the previous limits of traditional enterprise automation solutions. Businesses can use the technology to not only process structured data with defined rules, but also to automate human interactions, such as text and voice recognition, natural language processing (NLP) and text-based chat.

Second, the most advanced IA analytics now reveal what is meaningful, do it in real time and can also predict what is coming next – a huge asset to businesses striving for a competitive advantage.

Third, flexible and accessible IA allows the automation of tasks within existing procedures and leveraging existing infrastructure, without redesigning processes and making drastic changes in roles of human workers. Those automation projects are faster and easier to implement, so they are affordable for more organisations.

Fourth, the rise of the digital workforce has impacted the role of the human knowledge worker, who is becoming less of a ‘doer’, and more of ‘trainer’. Instead of performing a task themselves, human workers are now starting to think more about how to standardise and automate it.

“IA is one of the most pragmatic and impactful technologies that an organisation can implement as IT digitally transforms, especially when deployed strategically across an entire enterprise, rather than just as a tactical point solution,” says Mr Dening. “Large legacy organisations are using IA to modify their systems to facilitate a digital-first approach to the way they operate, allowing them to compete with today’s digital-native enterprises.”

In the view of John O’Brien, research director of intelligent application services at IDC Europe, IA is the answer to a range of workforce issues across the globe. “IA is starting to become a strategic priority for some advanced regions of the world that are now facing up to skills shortages and related socioeconomic pressures of ageing workforces and low birth rates, such as Japan, where we are seeing huge growth and some of the largest strategic deployments to date. However, that is the leading edge of the spear.

“For the majority of organisations, they are still at the point of inflexion where automation pilots and proof of concepts have been road-tested,” he continues. “It is now about how to get them to scale. A new breed of automation champions now has to engage the C-suite and a broader set of stakeholders to make this happen.”

Key challenges

While IA has many benefits, there are also challenges in deploying advanced technologies. According to research commissioned by Automation Anywhere, the five listed below are those that companies particularly need to overcome.

Technology. The challenge of scalability requires organisations to build a culture that can evolve as technology advances. A short-term vision would keep organisations stuck in small scale use-cases without looking at the broad benefits of automation and AI.

Skills. The future is all jobs ‘supported by automation’. By optimising for immediate productivity gains without creating a culture of support and advancing skills, organisations would see momentary increases in efficiency without long-term performance sustainability.

Diversity. Organisations need to have universal trust in automation and AI and ensure opportunities exist to use the technology among all genders.

Authenticity. The challenge is to avoid ‘AI washing’ – overstating the capabilities of the technology. The less workers trust the organisation, the harder it will be to market the technologies and realise the real value in the long run.

Resilience. Without embracing change, the technology will be slow to evolve as will worker’s skills, and an organisation’s diversity and authenticity.

“The biggest challenge with any IA project is scalability,” adds Mr Cutura. “Because the technology is not disruptive, businesses start by automating a thin slice of a process and that limits the return on investment (ROI). A thin-slice approach is good toward building or testing the technology. IA delivers best returns when used to automate an end to end, mature business process.”

That said, the numerous IA tools available means companies can struggle to identify the technologies that best suit their needs. “Some businesses try to apply automation to everything, and others have tried experimenting with AI and ML without an ROI analysis,” says Ajay Vij, senior vice president and industry head of financial services at Infosys. “There are also more specific data science challenges, such as making AI explainable and removing bias from algorithms, but these are now acknowledged by the industry and wider initiatives are being developed to improve this.”

Integration strategies

Given the complex nature of IA technologies, companies need to choose an appropriate integration strategy – a decision likely to boil down to whether this can best be performed by in-house staff or an external organisation.

“It is important for IA specialists to understand overall company objectives when embedding IA into their business models,” suggests Mr Cutura. “The best way to achieve this is by creating a Centre of Excellence (COE), where automation expertise lies, and use this to achieve the ultimate business goals. This expertise could be in-house or outsourced, as each has its own advantages. An outsourced model can leverage the expertise and experience of similar automation projects. It also offers the opportunity to scale up and down as required. On the other hand, in-house skills are advantageous in that there will be a more mature understanding of a company’s processes.”

In the experience of Chris Huff, chief strategy officer at Kofax, in-house automation is typically established by large enterprises that can afford the overhead of a cross-functional digital programme office,” he says. “Outsourcing tends to be a better fit for small and medium businesses and mid-market companies wishing to reduce infrastructure set-up costs, and the expenses associated with maintaining a proficient workforce of automation experts. While this is the current state, an emerging trend is beginning to surface whereby IA vendors create as-a-Service solutions that allow small and medium-sized businesses (SMBs) a financially viable way to adopt and scale.”

Whether in-house or outsourced, the key strategy, according to Mr O’Brien, is for companies to start small but think big. “This means engaging with all the stakeholders from the outset to get buy-in and build a strategy that can take you from A to B,” he suggests. “IA providers and their partners are now heavily invested in scaling adoption, and want to support enterprises on this journey.

“Technology specialists are partnering and acquiring technology to support these ambitions in areas that make it easier for non-technical users to design and build and run automations,” he continues. “Many companies are opting for COEs to retain and grow expertise internally, and service partners can support and train internal teams, albeit this often comes with a high price tag.”

Minimising costs

For the most part, introducing IA into existing processes and systems will have significant financial implications for companies, especially if it is rolled out as part of a larger digital transformation strategy.

“The IA space is heavily open source-driven and the major cost is around developing skill sets to implement IA,” says Mr Vij. “Enterprises can take advantage of ready-to-use, open source-based frameworks built for specific use cases, such as email handling, churn management, triaging, automated routing, customer service request handling, and speed up the time to market as well as productionise IA.”

According to Mr O’Brien, IA should be utilised in order to free up costs that can then be reinvested elsewhere. “Do not just see IA as a cost reduction exercise, as this is guaranteed to fail,” he believes. “Cutting costs should actually be seen as just one benefit. Enterprises need to take a longer-term view on this, to consider it as part of the modernisation agenda and the change that will be needed to be successful in the future.”

Once the decision to introduce IA has been made, one issue that companies may raise is the extent to which this could entail dismantling existing IT architecture, alongside protecting underlying systems.

“IA is non-disruptive technology and does not require businesses to dismantle existing systems,” says Mr Cutura. “Neither does it require expensive development to integrate with existing technologies in use. It helps break silos between various systems and get the best returns from your existing technology investment. It is a win-win from this perspective.”

Advancement and evolution

With IA technologies advancing exponentially, the question on many lips is just how far can IA conceivably go in helping companies improve business performance?

“IA will not replace human workers but empower them,” asserts Mr Dening. “Liberating workers from mundane and repetitive tasks frees them to think, create and innovate. That human element cannot be overstated, because those improvements to worker morale and wellbeing are what drive improvements to business. IA will enable digital experiences that drive greater efficiency and better end experiences for customers.”

Equally optimistic, Mr O’Brien believes that IA will continue to evolve and is here to stay. “In truth, it has been here since the industrial revolution,” he concludes. “It is being driven by the pace of technological change and we are in the midst of a number of potentially game-changing technology waves that will drive enterprise transformation performance. It is this foundation that will support how far IA can go over the coming years.”

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Fraser Tennant