Robots. Automation. Artificial intelligence. For many years, the best these fields could expect in a board room was thinly-veiled confusion – at worst fear and disquiet that they were helping to bring about a science-fiction dystopia. But times have changed. Today automation technology is a fast-growing field, attracting the brightest minds of our age to push the boundaries of how technology can assist and transform our daily lives. According to market research firm Statista, the global automation market is set to generate around $214 billion worldwide this year – up from $186 billion in 2019.
Businesses are drawn to automation for a variety of reasons. Some are attracted by the possibility of automating simple, repetitive processes, opening the door to valuable new efficiencies and cost-savings across the business. Others are even more ambitious. For example, some industrial giants are starting to use artificial intelligence (AI) to intelligently manage sensors and applications across the enterprise; rapidly analyzing the vast amount of data generated to create actionable insights. Covid-19 has only accelerated these trends, setting a breakneck pace for businesses – if they had not before – to embrace digital transformation. In fact, the Flexera 2021 State of Tech Spend Report shows that almost half of companies globally plan to increase IT spending this year, with almost 3 in 4 saying that they will spend more on automation and almost 2 in 3 for artificial intelligence (AI) and machine learning (ML).
Time and cost savings
The simplest and perhaps most rewarding benefit of automation is the amount of time and effort that businesses can save. Automation technology can be implemented to perform rule-based, repetitive tasks such as administration or data cleansing. Robotic process automation (RPA) is perhaps the most successful of these technologies, usually introduced to free up time for workers to focus on work that cannot be done by machines. A 2019 Deloitte survey of 523 organizations globally found that executives expected automation to increase their workforce capacity by 27 percent by 2022 – that’s equivalent to 2.4 million employees. By giving workers more time back, it ultimately enables business leaders to maximize the potential of their staff.
Furthermore, this capability can also be incorporated into business models to support employees in their work. Automating demanding, technology-based tasks, such as managing IT infrastructure, can provide employees with greater control and visibility of the framework they’re managing as it simplifies internal operations. Although certain processes will still require human input, automating system maintenance and configuration, for example, can greatly improve the proficiency of employees in managing networks. Many IT professionals are taking this journey one step further in the cloud, moving towards an effectively independent and self-healing infrastructure – monitoring, managing, and resolving infrastructural issues with minimal human input.
Improved data insights for better-informed decision-making
The race to become data-driven is very much underway. For many organizations, their data is one of the most valuable assets they possess. From front-end customer-facing operations to back-end network management, data provides the rich insights to keep businesses agile and deliver the intelligent, personalized experience users expect.
IDC estimated that more than 59 zettabytes (59 trillion gigabytes) of data was created, captured, copied and consumed worldwide in 2020. This figure, up from 33 zettabytes in 2018, gives a sense of the enormous challenge for businesses to efficiently analyze and secure benefits from this information. Network management can particularly struggle here, with IT professionals grappling with the huge quantity of status updates, alerts, and threat information that comes across their desks every day.
AI has a crucial role to play in overcoming this challenge. The processing power of AI enables organizations to rapidly analyze data at scale. Let’s consider network management. AI can assist security analysts in detecting and responding to potential threats such as ransomware, malware and data breaches. The predictive power of AI allows it to even start learning and recognizing patterns in network traffic, ensuring IT teams can plan ahead for variations in performance and protect against threats before they happen. Together, these use cases offer dramatic cost savings for the business, minimizing downtime and helping the organization become a data-driven, proactive and agile operation.
Similarly, there has been an emergent trend where Software-as-a-Service platforms are combined with AI to boost value from business data. This has been particularly transformative for customer experience, allowing firms to track customer relationships at scale, analyze patterns in their behavior and recommend the best way to interact with them. The result is a more personalized service for customers, and a more streamlined and ultimately profitable operation for the business.
Indeed, to get the most out of automation, RPA can be combined with AI to create intelligent automation. This enables a series of computerized processes to work in tandem to carry out simple tasks whilst accumulating and analyzing data at a much faster rate. Deloitte judged that organizations that have already implemented intelligent automation at scale have benefitted from a 27 percent cost reduction.
Augmented employee capabilities
Popular discussion of AI still starts from the default position of the technology inflicting mass job losses, with robots replacing humans. Yet more and more research is showing that AI will actually be a net positive for the economy. The World Economic Forum predicts AI will create 97 million new jobs by 2025, compared to 85 million losses. This new understanding is starting to have an effect on public debate. Recent trends identified by Adobe Digital Insights show more people discussing robots and jobs online, but crucially in a positive rather than negative light.
AI is best seen as a complement to human capabilities, rather than a replacement. Machine intelligence provides humans with a formidable analytical tool, able to process vast quantities of data in a matter of seconds and produce rich insights. Humans can then consider the resulting intelligence about the data, interpreting its significance and use it to plan and take action – elevating the quality of human decision-making. It is this appreciation of context and causal analysis, understanding on an intrinsic level the link between one factor and another, that truly distinguishes humans from AI.
As Brian Bergstein recently set out in MIT Technology Review, “AI’s ability to spot correlations – e.g. the clouds make rain more likely” relies on the algorithm crunching often millions of data points and then predicting an outcome. What they lack is the “common sense” humans possess to instinctively know the expected result from an action – let alone the ability to “reason about why things happened and ask ‘what if’ questions.”
Finally, there is plenty of reason to believe that a human-AI workplace will be a better place to work. By freeing employees up to focus on more meaningful tasks and augmenting their capabilities in the workplace, businesses will start to see a more productive and engaged workforce emerge. Boosting employee satisfaction is not just a ‘nice-to-have’. Gallup found that high engagement business units are 21 percent more profitable on average. With businesses in the tech industry facing a global digital talent shortage, keeping employees satisfied through automation could be a step in the right direction for organizations struggling to attract and retain their staff.
Delivering the business value of automation
Whilst the road to implementing automation across a business is far from simple, here’s seven steps to put you on track for success:
1. Take your time
Don’t rush, spend the time scoping out the areas of the business that would benefit from automation and plan out a roadmap for making it a reality.
2. Don’t forget about data
Data quality is vital for the success of an AI program, and businesses need to invest in bringing their data up to scratch for its intended purpose – issues of racial bias in some AI programs often stem from narrow or prejudiced ideas creeping into the training data.
3. People matter
Automation can be a disruptive moment of transition for the business, so be transparent, ensure everyone understands their role in the automated workplace, and help employees gain the skills to adapt to this new world.
4. Continuous improvement
Assiduously track the impact of automation from the start, taking into account any technical and staff concerns to ensure it keeps playing the most effective role in the business.
5. Keep innovating
The future is AI, so why not put your business ahead of your competitors and make your organization a hub of AI innovation – identifying new use cases, connecting with the wider AI ecosystem, and fostering the next generation of AI talent.
Automation cannot be viewed in the future tense anymore. It is here, it is revolutionizing the economy, and businesses cannot afford to be left behind. Little wonder then that 84 percent of executives and analysts from around the world told MIT and Boston Consulting Group that they believed AI will enable them to ‘obtain or sustain a competitive advantage.’
There is no one size fits all approach for automation. Businesses looking to capitalize on the benefits of automation have plenty of options available to start delivering meaningful value to their business, and with innovation accelerating every year, that list is only set to grow.
Sim Sabharwal, Global Director, Network Infrastructure, Ensono