Posted: 21 Sep. 2020 8 min. read

Potential: AI and superteams

In this blog post we explore the second element of the 2020 Human Capital Trends report: Potential. Oscar Hamilton, Director and FSI Digital Finance Transformation Lead, and Gloria Viedma Navarro, Senior Consultant, discuss how AI can be used to establish consistency, increase productivity and unlock value in teams.

AI as the future!

AI itself is a broad term. It refers to human-like intelligence in machines and offers a spectrum of capabilities. Within AI, organisations have been moving up the spectrum in the last ten years at different speeds, starting on the journey with RPA, moving into cognitive technologies to understand documents, sight, voice or process. Deep learning, neural networks and part of AI are less taken up by organisations and are primarily used for some specific use cases. Some organisations are even struggling with more basic forms of automation, such as RPA. An annual survey around automation, in 2019, found that only 8% of organisations have achieved scale with RPA. I think this also shows that although some organisations are trying to explore new technologies, there is still a lot of work to be done to really overcome barriers when trying to master the basics.

Also, as the adoption of AI evolves over time, we’ll increasingly harness the power and insight of data using the cloud. This will accelerate when compute power reaches new levels with quantum computing - one day in the future! It’s really exciting to think about the possibilities if you combine this deep, rich data set that automation and AI can provide, to create a digital twin of an organisation, and use that to run simulations to test different scenarios, in the same way that Formula One teams simulate scenarios to plan their race strategy.

AI’s impact on humans

In Fourth Industrial Revolution, automation is fundamentally changing and this is creating a need for new skills and new capabilities, and makes workforce transformation efforts very crucial. RPA automates the manual, repetitive, rules-based tasks that are typically associated with less skilled jobs, and provide the lowest levels of job satisfaction in the workplace. When an organisation is driving their intelligent automation programme or is exploring new technologies, it’s important that it’s taken into consideration within a wider workforce reskilling and upskilling. In order to do this the workforce needs to be prepared to work in a completely different way because when automation is implemented, we’re essentially changing the way work gets done. The team structure, capabilities and skillsets that will be required drive this future is very different.

Automation is augmenting the human workforce. It’s freeing up time to allow humans to do more value-add work and leaving the repetitive, less value-add tasks to the bots. Also, when an organisation starts scaling its automation initiatives or digitisation projects, it will create more job opportunities in order to drive and maintain that automation strategy.

It can be quite difficult and quite daunting for some companies to adopt and understand new automation technology. Organisations need to figure out how they use different technologies together, in the right way, to work well with people. It’s often much faster and more effective to move to outsourcing automation capabilities to providers, Deloitte’s DARA platform and digital work is a great example of this.

Consistency, productivity and unlocking the value

Many organisations are finding it difficult to realise the full potential of automation and AI. Organisations can unlock huge value through automation - far beyond productivity. Automation doesn’t happen in a vacuum. Initially, the motivation to start on an automation journey might be to increase productivity and achieve consistency. However, there can also be a real impact beyond this.

Deloitte recently worked with a large hospital in the UK to develope an AI solution that improved the triage of general practitioner referrals. The aim was to use AI to unlock the data held in electronic medical records. It allowed for more efficient processing, intelligent analysis, and improved decision-making in order to overcome some of the service challenges that the department had been experiencing. It suggested the most likely triage outcome, and then the urgency status and clinic or diagnostics for referral. The impact was hugely positive. There was a 15% increase in speed, and a 15% to 20% reduction in the number of patients added to a waiting list. This shows that beyond productivity, there’s a massive potential for unlocking value - positive value for those patients. Here, AI enabled better decision-making to identify patients who possibly had cancer earlier, so they got faster triage, and they were seen by specialists which is potentially lifesaving.

Automation should be rooted in driving up business value by understanding what the business needs and aligning to that. Deloitte looks at value across key value levers of cost, speed, quality, and experience and however, each organisation has their own mission and vision statement which should align with their automation efforts. Organisations should also know how they can use AI to move beyond task-based automation to get much more value through hyper-automation and end-to-end automation.

To achieve the most value organisations must reengineer processes, improve how teams work, improve how processes are run, and not just work on a specific bit of a process, but look end-to-end. Deloitte has also delivered an automated end-to-end complaints process at a major bank. In phase one we implemented a small number of point automations using bots to get some quick wins and prove the technology worked. In phase two, the underlying platforms were updated, and a workflow was put in place to drive better end-to-end control with further automation. In phase 3, we then used the power of the data of those bots. We put it in an analytics platform, which actually took 1,300 variables and used those to identify which complaints which were actually at high risk. This insight, using the data that was provided from automation, provided better insight and reporting to the business. Now customers were able to self-serve and understand where their complaint was in the journey.

Robots and AI

It’s interesting to see how different technologies can help augment humans in different ways. Technologies like RPA which are more task-based and rule-based, or there’s AI that imitates a human reading vision and enables better decision-making. A term for this within Deloitte is the ‘Age of With’, humans with machines.

When thinking about robots, it depends on the type of robot and the different functions it can perform. RPA does exactly as it’s told but AI requires data and information. Things become complicated because it evolves with time and changes as you feed it different information, so models need to be upskilled. Feeding in data sets is important for this to work, it these kinds of robots will learn different things depending on what information we feed them.

As organisations scale automation they will need to design and set up how to orchestrate and run automations, and understand how to drive continuous improvement from that workforce - we see automation as digital workers rather than technology. Someone will have to have the responsibility of orchestrating the robot workforce. Typically, this does require a centre of expertise, or excellence, in order to understand the data that the robots or the automation are providing, and to drive end-to-end process performance and improvement. It is important to develop the right automation capabilities and to keep them upskilled in the same way as your upskill the human workforce.

Merits and demerits of automation

Automation is inevitable and it is all around us. Automation needs to be designed so that people and machines work together in the right way. All the apps like dating apps, transport apps, banking apps, etc. are enabled through automation.

While implementing automation in an organisation, it is important to communicate well with the workforce and be clear about your ambitions, strategy and the reason for pursuing automation. Communication is vital to engage the workforce and mitigate any adverse reactions.

Along with this there are lots of unanswered questions that organisations will need to address such as the potential for bias in AI which can discriminate against a particular gender, ethnicity, or certain demographics. Also, on a societal level, it is important to think about reskilling the workforce, so that their skills remain relevant and they can be a productive, future workforce.

Resilience in a world of AI and of huge changes

The COVID-19 pandemic has really shown that if organisations and people need to change, they can – and rapidly. Many people within a day, went from working in an office environment to remotely working and thriving whilst doing so. Resilience at an organisational level includes an organisations’ employees and technologies. It’s the ability to thrive and adapt in difficult times, or in times of massive change, but really having that perfect marriage between tech and people that allows you to do so.

For more Future of Work insights, check out our Humanising the Future of Work podcast

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Oscar Hamilton

Oscar Hamilton

Director

Oscar leads FSI Digital Finance Transformation within Deloitte. He has led or delivered some of the Financial Services Industry’s most complex technology enabled Finance Transformations and has worked closely with Ledger, Reporting and Consolidation platforms, Robotics Process Automation, Cognitive and Artificial Intelligence. Oscar has successfully delivered scale robotics programmes in Finance for the past 2 years, including the largest Finance robotics implementation in FSI.