Capgemini: scaling AI initiatives to improve efficiency
Within that time, more than half (53%) of organisations have moved beyond AI pilots, an increase of 17% since which reported 36%. In addition the latest research also reports 78% of leaders are continuing to progress their AI at scale initiatives at the same pace as before COVID-19, while 21% have increased their deployment pace.
In contrast 43% of organisations struggling due to COVID-19 have pulled their investments into the technology, while 16% have suspended aii AI initiatives due to high business uncertainties due to COVID-19.
Capgemini’s report titled ‘’ revealed that the successful implementation of AI at scale delivers significant topline benefits including: 79% of leaders seeing more than 25% increase in sales of traditional products and services; 62% of leaders seeing at least a 25% decrease in the number of customer complaints; and 71% witnessed at least a 25% reduction in security threats.
When it comes to the adoption of AI, Capgmeini’s life sciences and retail organisations are making up 27% and 21% of AI at scale leaders respectively, followed by automotive and consumer products (17%) and telecommunications (14%). Comparing sectors that have suspended or pulled their investment in AI due to COVID-19, only 38% of life sciences organisations have had to suspend or pull their investment, compared to insurance (66%), banking (64%) and utilities (64%).
Capgemini notes that “this reflects in today’s context, where virtual assistants, contact tracing apps and chatbots are proliferating as organizations, like the World Health Organization, launch AI-based tools to gather as well as provide information during the ongoing pandemic.”
The essentials for scaling AI technology
Trusted and quality data
Leaders in scaling AI rank ‘improving data quality’ as a number one approach to generate more benefits from their AI systems. Having a strong data governance ensures that AI teams have the right quality of data and helps to improve the trust executives have in data. “Establishing the required technology platforms, such as a hybrid cloud architecture and democratising the data access, serve as core building blocks for scaling AI,” noted .
Having a dedicated AI lead
The research conducted by Capgemini reported that 70% of organisations find that a lack of mid to senior level talent a major challenge when scaling AI. More than half of leaders scaling AI (58%) have appointed an AI head, lead or chief AI officer to provide development teams with a vision, as well as establish guidelines relating to priorities, ethics and security, and harmonise the use of platforms and tools for developing AI.
“Organisations also need to focus on a wide range of skill sets for scaling AI applications, beyond pure AI technical skills, to include business analysts and change management specialists. However, there is currently a significant gap between demand and supply in important disciplines like machine learning or data visualisation,” added Campgemini. As a result, training and upskilling are critical in order to address the gaps.
Ethical AI interactions
Regardless of whether a company has a strong consumer and regulatory focus on ethical AI, Capmgeini’s research found many organisations are not actively addressing issues that require an empowered ethics team. The report highlighted 29% of struggling organisations compared with 90% of AI leaders agreed that they have a detailed understanding of how and why AI systems produce the output they do.
“This is important for business executives to be able to trust organisational AI systems. At the same time, it is impossible to establish consumer trust if the customer-facing employees lack trust in the models or data organizations use.”
Four principles for successful AI
Within the report Capgemini also highlighted four principles it recommends businesses looking to scale their AI to focus on:
- Empowerment: building strong foundations to provide easy access to trusted, quality data via the rights tools and platforms
- Operationalise: deploying AI with the right operating model, prioritise initiatives and ensure well-balanced governance and ethics
- Nurture: develop talent and collaborate with ecosystems and partners
- Monitor and amplify: continuous monitoring of the models accuracy and performance to deliver and amplify business outcomes
“In light of the recent COVID-19 crisis, while organisations are looking at data and AI to bring resilience to their operations, there is an even stronger need for connections between tactical and strategic business objectives and implementation in order to achieve scale,” says Anne-Laure Thieullent, Artificial Intelligence and Analytics Group Offer Leader at Capgemini.
“Our research highlights that the most successful organisations combine efforts to rationalise and modernise their data landscape and data governance processes, focus on bringing new agile tools from partners ecosystems as well as approaches like DataOps and MLOps to develop and deploy AI solutions, nurture teams from diverse backgrounds, and set up balanced operating models.”
Automation of repetitive tasks leads to higher value work
Two-thirds of global office workers feel they are constantly doing the same tasks over and over again. That’s according to a new study (2021 Office Worker Survey) from automation software company UiPath.
Whether emailing, inputting data, or scheduling calls and meetings, the majority of those surveyed said they waste on average four and a half hours a week on time-consuming tasks that they think could be automated.
Not only is the undertaking of such repetitious and mundane tasks a waste of time for employees, and therefore for businesses, but it can also have a negative impact on employees’ motivation and productivity. And the research backs this up with more than half (58%) of those surveyed saying that undertaking such repetitive tasks doesn’t allow them to be as creative as they’d like to be.
“When repetitive, unrewarding tasks are handled by people, it takes time and this can cause delays and reduce both employee and customer satisfaction,” Gavin Mee, Managing Director of UiPath Northern Europe tells Business Chief. “Repetitive tasks can also be tedious, which often leads to stress and an increased likelihood to leave a job.”
And these tasks exist at all levels within an organisation, right up to executive level, where there are “small daily tasks that can be automated, such as scheduling, logging onto systems and creating reports”, adds Mee.
Automation can free employees to focus on higher value work
By automating some or all of these repetitive tasks, employees at whatever level of the organisation are freed up to focus on meaningful work that is creative, collaborative and strategic, something that will not only help them feel more engaged, but also benefit the organisation.
“Automation can free people to do more engaging, rewarding and higher value work,” says Mee, highlighting that 68% of global workers believe automation will make them more productive and 60% of executives agree that automation will enable people to focus on more strategic work. “Importantly, 57% of executives also say that automation increases employee engagement, all important factors to achieving business objectives.”
These aren’t the only benefits, however. One of the problems with employees doing some of these repetitive tasks manually is that “people are fallible and make mistakes”, says Mee, whereas automation boosts accuracy and reduces manual errors by 57%, according to Forrester Research. Compliance is also improved, according to 92% of global organisations.
Repetitive tasks that can be automated
Any repetitive process can be automated, Mee explains, from paying invoices to dealing with enquiries, or authorising documents and managing insurance claims. “The process will vary from business to business, but office workers have identified and created software robots to assist with thousands of common tasks they want automated.”
These include inputting data or creating data sets, a time-consuming task that 59% of those surveyed globally said was the task they would most like to automate, with scheduling of calls and meetings (57%) and sending template or reminder emails (60%) also top of the automation list. Far fewer believed, however, that tasks such as liaising with their team or customers could be automated, illustrating the higher value of such tasks.
“By employing software robots to undertake such tasks, they can be handled much more quickly,” adds Mee pointing to OTP Bank Romania, which during the pandemic used an automation to process requests to postpone bank loan instalments. “This reduced the processing time of a single request from 10 minutes to 20 seconds, allowing the bank to cope with a 125% increase in the number of calls received by call centre agents.”
Mee says: “Automation accelerates digital transformation, according to 63% of global executives. It also drives major cost savings and improves business metrics, and because software robots can ramp-up quickly to meet spikes in demand, it improves resilience.
Five business areas that can be automated
Mee outlines five business areas where automation can really make a difference.
- Contact centres Whether a customer seeks help online, in-store or with an agent, the entire customer service journey can be automated – from initial interaction to reaching a satisfying outcome
- Finance and accounting Automation enables firms to manage tasks such as invoice processing, ensuring accuracy and preventing mistakes
- Human resources Automations can be used across the HR team to manage things like payroll, assessing job candidates, and on-boarding
- IT IT teams are often swamped in daily activity like on-boarding or off-boarding employees. Deploying virtual machines, provisioning, configuring, and maintaining infrastructure. These tasks are ideal for automation
- Legal There are many important administrative tasks undertaken by legal teams that can be automated. Often, legal professionals are creating their own robots to help them manage this work. In legal and compliance processes, that means attorneys and paralegals can respond more quickly to increasing demands from clients and internal stakeholders. Robots don’t store data, and the data they use is encrypted in transit and at rest, which improves risk profiling and compliance.
“To embark on an automation journey, organisations need to create a Centre of Excellence in which technical expertise is fostered,” explains Mee. “This group of experts can begin automating processes quickly to show return on investment and gain buy-in. This effort leads to greater interest from within the organisation, which often kick-starts a strategic focus on embedding automation.”