May 19, 2020

How to push past the ‘hAIpe’ and get going with AI

Technology
Artificial intelligence
AI
Tuomas Syrjänen
5 min
How to push past the ‘hAIpe’ and get going with AI

When it comes to the gap between hype and reality, the business community’s approach to AI is hard to beat. A recent report by Microsoft found more than half of UK companies have no AI strategy in place. This situation seems to be mirrored across Europe, with Information Age recently suggesting that the continent is at risk of becoming AI ‘has-beens’.

Part of the problem is that the hype about what AI is and what it can do can make it hard for businesses to know how to apply this transformational technology to their own organisations. Based on our own experience of embracing AI, here are five tips to help businesses cut through the hype and discover AI’s benefits at first hand.

1. Understand AI and how it fits with business strategy

Currently AI experiments tend to be random efforts to understand how the technology works with very little attempt to link them to an organisation’s broader strategic context. Companies considering adopting AI should start by identifying their value levers by asking what business are we in and what makes us successful? Is it R&D? Marketing? Customer service? Cost efficiency? Once these levers are clear, AI can be applied to enhance these critical dimensions of the business. This strategic focus is crucial due to the management focus, data infrastructure and cognitive investment that implementing AI requires.

With the value levers identified and matched to AI’s capabilities, companies are better placed to identify problems to solve that align with their strategic priorities. For example AI can help with forecasting (such as predicting budget overrun or periods when staff will be sick.) In sectors such as retail, project management or healthcare, where the value levers feature a strong customer focus, AI can help to visualise and improve how businesses plan and optimise resources across different scenarios.

AI is also great at knowledge management: Where value levers are based around innovation and R&D, AI-enabled search engines can make the competencies, knowledge base and ideas of a company’s entire workforce visible quickly and then harness these to the data available within the company. This helps to build teams with augmented know-how who are equipped with the depth of knowledge and data to generate new insights and achieve a much greater impact in a much shorter period of time.

2. Assess how AI-ready your business is

What is your company’s AI maturity level? We estimate that 80% of time spent on AI involves working with data: getting access, cleaning, preparing, pre-processing, normalising: the grind that precedes the more ‘fun’ stuff - designing interesting AI applications.

Businesses need to discover what data they have, including data from unusual or unexpected sources such as staff surveys or financial results. Where is the data located? Is it cleansed, correlated, linked and machine-readable? If not, are there guidelines and processes for doing so? Do existing systems and workflows need to be redesigned to make them easier to use and integrate with AI?

Companies that have assiduously collected customer data are ready to consider how AI could deliver monetisable insights. This includes using AI to extract and combine data from unusual sources to reveal unexpected insights which could form the starting point for new products/services or ways of working.

Putting the right data infrastructure in place for all this will take significant investment for a company - simply relying on a “data lake” system won’t be enough. This is another reason why AI needs to be applied in a strategic context, to ensure the infrastructure will eventually deliver a return on investment for the business.

3. Champion the techies!

Benefiting from AI will be tough if data scientists and technologists aren’t integrated into the heart of your business. Tech specialists need to understand and buy in to the commercial importance of their work while senior leaders need to have a meaningful understanding of what tech teams actually do. This doesn’t mean learning to write Python code, however AI implementation does require understanding that there are different  types of algorithms for different tasks and the pitfalls and the trade-offs of each.

Bringing data scientists and technologists together with sales/business development teams and creative teams, while ensuring the C-suite understands the fundamentals of AI, will mean AI projects have a much greater chance of success as they will be rooted in what is technologically feasible and commercially viable.

4. Start small, but scale quickly

Having agreed how AI fits into the overall business strategy, it’s time to start with small experiments that can deliver results quickly. Senior leaders should work with data scientists to identify small problems which AI could help solve. This could include using AI’s automation capabilities to take over logging of invoices or using its pattern recognising functions to help identify why certain teams may be underperforming. They should then take what they learn and iterate their approach to maximise its value. This approach not only minimises risk, it also provides insights into the challenges of integrating AI into a business. At the same time as experimenting with AI in small ways, business leaders should deploy horizon thinking to imagine how it can be used to identify new revenue sources, expand into new sectors and even redefine what business the company is in.

5. Boost your team’s adaptability quotient 

AI is ushering in an era of human-machine collaboration requiring a radical rethink of traditional operating models, role definitions, individual success measures and career progress. For some businesses and their people, this translates reductively into fears about job cuts. In practice, we see an AI-enabled workforce as one where people are supported to continuously learn about new technologies and about societal and behavioural changes and where autonomous teams will be empowered to adapt quickly to market or environmental changes.

To transition to this vision, leaders need to assess how teams can be encouraged to buy into an AI-enabled future. Unless companies understand and adapt to AI’s cultural impact, they won’t be able to change gears operationally. And eventually that systematic failing will translate into an inability to identify and solve problems for customers.

With AI considered by many to represent a fourth industrial revolution, it inevitably attracts a degree of myth and hype. If businesses can look beyond this and take these first steps to integrate the technology into their organisations, the true transformative potential of AI will emerge.

Tuomas Syrjänen is the co-founder AI Renewal at digital engineering and innovation consultancy Futurice

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May 28, 2021

Automation of repetitive tasks leads to higher value work

Automation
UiPath
technology
repetitivetasks
Kate Birch
4 min
As a new report reveals most office workers are crushed by repetitive tasks, we talk the value of automation with UiPath’s MD of Northern Europe, Gavin Mee

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.

  1. 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
  2. Finance and accounting Automation enables firms to manage tasks such as invoice processing, ensuring accuracy and preventing mistakes
  3. Human resources Automations can be used across the HR team to manage things like payroll, assessing job candidates, and on-boarding
  4. 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
  5. 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.”

 

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