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The Autonomous Enterprise: Intelligence at the Core



The start of a new year is a critical time for all businesses and enterprises: It is a time to make changes and adjustments, explore and introduce innovative ideas, and set new goals and benchmarks for the year ahead. The start of 2021 brings a unique meaning to this often-used approach; after all, we’ve overcome so much in such a short amount of time living in this “new normal.”

The new normal has quickly taken hold during these unprecedented times, and businesses have taken bigger steps toward becoming autonomous enterprises. These companies recognize the need to drive resilience along with efficiency. Leveraging artificial intelligence (AI), machine learning (ML), and automation is not only becoming an essential component to the success of large-scale corporations’ operations, but it is also helping reshape roles within the IT industry. By adopting these technologies, you can create a more intelligent, agile, and responsive business model.

Simplifying technology management is one of the most frequently cited challenges raised by our customers. And the answer is not as complex as you may imagine. Businesses mainly spend their revenue on running enterprise operations, but most of these operations are managing innovations of the past. Working toward becoming an autonomous enterprise brings new levels of context, intelligence, and automation to day-to-day processes and decision making at a much faster pace.

Digitate is pleased to sponsor this research by Harvard Business Review Analytic Services, which explores how organizations are integrating AI/ML and automation skills and how this improved approach is delivering meaningful impact in enterprises across industries.

Businesses have been using digital technology to automate the workplace for more than half a century, helping them get work done faster, safer, and more reliably. Now, greater gains may be on the horizon. Like self-driving cars, an autonomous enterprise that largely runs itself no longer seems such a fanciful idea.

Building on powerful technologies like cloud computing, the internet of things, machine learning (ML), and other forms of artificial intelligence (AI), companies are automating a growing number of business activities—from processing insurance claims to managing corporate IT systems—that once required a human at the helm. As these processes multiply, combine, and connect, companies themselves move ever closer to autonomous operation. Digitally native organizations like Amazon and Uber hint at what’s possible. “If you look at those two companies, they are essentially websites acting as fulfillment centers,” says Vijay Bathija, vice president of commercial strategy and enterprise analytics at Etihad Aviation Group, an airline based in Abu Dhabi, United Arab Emirates. “With Uber, it’s not the taxi driving the app; it’s the app driving the taxi. By contrast, we are an airline driving a website—not a website driving an airline. But we talk in terms of making that transition.”

To be sure, the goal of creating a fully autonomous enterprise is a long way off, especially for large business enterprises with far-flung and complex ecosystems. But even the incremental rewards available to companies as they build toward that goal could be substantial—and much welcomed. For all the advances in technology over the past two decades, gains in productivity have been trending lower1 in most developed economies, and a majority of organizations still spend vast amounts of time and resources on day-to-day operations that are not core drivers of value. According to one multinational survey, the average office worker spends 552 hours annually completing administrative or repetitive tasks, or about a third of their work year.2 It seems that a great deal of innovation has been aimed not so much at finding new ways of doing business but rather at squeezing more efficiency out of yesterday’s practices—at speeding up the conveyer belt rather than eliminating it.

With the rapid maturation of increasingly sophisticated technologies, enterprises now have an opportunity to bring new levels of context, intelligence, and automation to day-to-day processes and decision making in a way that spans organizational silos and enables holistic, enterprise-wide change. In short, they can work toward becoming an autonomous enterprise.

Transformation of this sort will require a deep understanding not only of the potential of new technologies but also of how existing information systems connect and interact and where current business processes have room to improve. Without those deep insights, it will be difficult to determine where opportunity lies and where existing IT infrastructure might be holding an organization back from realizing its full potential.

“There are going to be lots of starts and stops based on what people are trying to achieve with automation,” says Maureen Fleming, program vice president for worldwide intelligent process automation at International Data Corp., a provider of market intelligence and advisory services in the tech sector. “But you can already see progress accelerating.”

While our primary objective was to reduce risk, we also knew that automating would improve our productivity and allow some of our talented employees to shift to higher-value work. These [improvements] ultimately will lead to better customer service and higher revenue growth,” says Bala Puvitharan at Multimatic Inc.

What’s Driving Automation Initiatives

While few companies explicitly talk about becoming an autonomous enterprise—as noted, the complete realization of the autonomous enterprise is a long way off—some do, at least in discrete areas of the business.

“As it relates to technology, we certainly think in terms of creating autonomous operations,” says Mohamed El Fanichi, chief information officer at Landmark Group, a multinational retailer based in Dubai, United Arab Emirates. “It is part and parcel of our lexicon. We have a center of excellence for robotics and automation that looks at every aspect of our organization to drive efficiencies, and our board of directors is updated every quarter on its progress.”

Efficiency and cost savings are the core drivers of automation initiatives at most organizations. As Etihad’s Bathija notes, the airline industry, to take just one example, operates with thin margins even in the best of times, so opportunities to boost productivity and reduce costs can never be ignored.

“To load an organization with costs it doesn’t need, especially in cash-sensitive businesses, is asking for trouble,” agrees Landmark’s El Fanichi.

But increasingly, companies also see that autonomous operations can provide a route to greater agility, reduced risk, a better customer experience, and, ultimately, stronger growth.

Consider privately held Multimatic Inc., a Canadian supplier of engineered components, systems, and services to the global automotive industry. When Bala Puvitharan joined the company in June 2019 as its chief information officer, one of his first goals was to reduce operational risk embedded in the company’s multiple enterprise resource planning systems. He has sought to reduce risk in part by automating the monitoring and maintaining of those systems to avoid glitches that could cause downtime in manufacturing operations.

“While our primary objective was to reduce risk, we also knew that doing these things would improve our productivity and allow some of our talented employees to shift to higher-value work,” Puvitharan says. “These [improvements] ultimately will lead to better customer service and higher revenue growth.”

Viswanathan Krishnamurthi, vice president of information technology at Eaton Corp., a multinational power management company domiciled in Dublin, Ireland, also sees the primary objective of automation as improving overall efficiency and productivity. “But we also look at what second-order benefits might spill over and how they can impact the customer experience, whether in terms of how easy it is to do business with us or how we create products that better meet our customers’ needs,” Krishnamurthi says.

In 2020, the Covid-19 pandemic accelerated the automation agenda at many organizations. At Etihad, it spurred increased efforts to create touchless experiences for its customers, including enabling them to update the status of their Covid-19 testing via the company’s website prior to flying. Recognizing the need for rapid decision making in this year’s fast-changing operating environment, Bathija adds, Etihad also was able to consolidate 11 different internal reports for its senior executives into one that goes out automatically every morning, in part by automating many of the underlying processes. It completed the task in six months, something that in ordinary times Bathija estimates might have taken a couple of years.


A Blueprint for an Autonomous Enterprise

The abundance of data, computing power, and artificial intelligence/machine learning (AI/ML) algorithms have created opportunities for enterprises to fundamentally reimagine how they drive customer experience, agility, and resilience—and ultimately become autonomous. An autonomous enterprise is characterized by its ability to learn and adapt to changing situations impacting the business landscape and, by automating and integrating processes, mimic human thinking and actions in an intelligent and consistent manner. One of the defining aspects of maturity in this area is the enterprise continuously reducing dependency on human intervention while driving exponential business changes.


An autonomous enterprise is driven by the “CIA” triad of key principles: context, insights, and actions. Context refers to the structural and behavioral model of the enterprise; insights are generated by applying AI/ML to operational data; and actions refer to applying intelligent automation to proactive, preventive, and reactive situations.

An autonomous enterprise is characterized by its ability to learn and adapt to changing situations impacting the business landscape.

Through these principles, organizations can become autonomous. Being truly autonomous means enterprises have developed and cultivated a strong data foundation and have applied AI/ML and intelligent automation technologies to business processes and their corresponding operations and interactions with stakeholders. 


Business leaders should not dismiss the idea of becoming an autonomous enterprise as an unattainable goal. In fact, now is an  opportune time for business leaders to embrace and leverage these technologies and processes. Doing so will help them deliberately march toward attaining the vision of becoming an autonomous enterprise, characterized by self-learning and the ability to adapt and automate. As enterprises start this journey, they should establish well-defined benchmarks and stages that enable the business to evolve.


An autonomous enterprise needs the following building blocks for its infrastructure, which can be applied to business processes and operating systems across functions:

  • Observability: The ability to understand the internal and external state of processes and systems by interrogating, inferring, and measuring telemetry data
  • Data collection and mining: Integrate and share data across different parts of the enterprise and aggregate it to learn the structural and behavioral model of processes and systems
  • Visibility: Structural and operational visibility of people, processes, and technology
  • Intelligent analytics: Detect patterns, build normal behavior models, and reason about situations and proactively identify risks
  • Intelligent automation: Automate actions in business processes
  • Communications: Enable collaboration and intelligent notifications

These capabilities must be actively developed as part of the overall core management-and-development fabric of the enterprise.

A standardized enterprise platform approach can enable uniformity and accelerate an organization’s journey toward becoming autonomous while emphasizing its focus on change management. Enterprise architecture frameworks and approaches help leaders embrace the concept of the autonomous enterprise and plot a focused transformation journey through set phases as their organization builds greater self-sufficiency in its core business processes.

With the rapid maturation of increasingly sophisticated technologies, enterprises now have an opportunity to bring new levels of context, intelligence, and automation to day-to-day processes and decision making.

Automation Initiatives Span the Enterprise

Businesses are pursuing automation initiatives on a broad front. Eaton has established what it has identified as four pillars of digital value creation centered around data monetization, partner ecosystem development, digital factories, and business process efficiency, with the latter two particularly aimed at automating operations.

“To a great extent, the focus over the past few years has been around our global shared services centers for corporate functions because we have a large number of employees in those centers doing highly repetitive, manual work,” says Eaton’s Krishnamurthi. “That’s been our initial target. But now we’re also branching off to try to address similar challenges in our business operations, including on the shop floor, as part of our effort to create digital factories.”

Eaton sees itself moving step by step to higher levels of autonomy, much the way the automotive industry has moved in stages toward the development of self-driving cars. Car companies started with driver-assistance tools like adaptive cruise control, then added higher-order systems that could control steering and acceleration under a driver’s watch, followed by technologies like automatic braking and lane-keeping assistance that can intervene if something goes wrong. Now, self-driving vehicles are being tested as automakers work toward delivering fully autonomous vehicles that won’t need steering wheels, or acceleration or brake pedals, because they won’t have human drivers at all.

“We are tracking our digital maturity in terms of how automated our processes are, and how integrated they are, and how much we are being able to leverage data for decision making, as we try to progress from where we are on the maturity path today to achieving our goal of full end-to-end automation, which is going to take some time,” Krishnamurthi says.

Multimatic, as noted earlier, is focused on automating manually intensive back-office business processes and IT operations, but also is moving toward automating more of its operational activities, including plant and equipment maintenance.


Contextual Knowledge and AI Fuel Autonomous Enterprises by Abhijit Mazumder, CIO, Tata Consultancy Services

Resilient, empowered, scalable, and adaptable—this is how the autonomous enterprise will be characterized and recognized in the future. In the Age of Business 4.0—a Tata Consultancy Services (TCS) framework to help organizations leverage digital technologies to address their transformation agendas as the next wave of change sweeps the world—a multitude of new opportunities for companies have emerged from the abundance of data, algorithms, and digital interactions. To deliver exponential value through these opportunities, businesses need to take ideas to market faster by automating their operations and fostering real-time, intelligent, and interconnected ecosystems. A TCS global survey on the impact of Covid-19 has revealed that leveraging intelligent automation in core business processes is a significant way for enterprises to achieve these goals.

Managing information and human interactions is critical to the success of an autonomous enterprise. While internet-of-things-based (IoT-based) sensors automate data collection, remote monitoring with mobile access points can mimic human efforts. By adopting and leveraging technologies like machine learning, natural language processing, unstructured data extraction (from documents and social media), cognitive self-services, and advanced analytics, the enterprise can transform its infrastructure and deliver unparalleled employee and customer experiences. Ensuring success requires substantial investment in automating processes and bringing in intelligent systems that can learn and repair themselves.

As humans work on mastering a specific business domain, over time they can develop a deep knowledge of organizational processes and their complex interactions. This contextual knowledge will play a crucial role in simplifying complex business processes by breaking them into bite-sized elements. Later, these processes can be streamlined and automated repeatedly, thereby enabling perpetual process transformation that supports exponential growth rather than just optimization and cost savings. For example, in traditional finance and accounting process optimization, the focus is on reducing days of sales outstanding (DSO) and reducing order-to-pay time duration, just as TCS reduced its DSO by 15% in the past five years. An integrated approach, though, aims to reduce working capital blockage and enhance customer experience by improving the payment reconciliation process and creating exponential value for stakeholders.

Enterprises have taken a quantum leap in digitization and automation to enable the remote work model, both for internal operations and for interactions between customers and business partners. The major challenge in becoming autonomous, though, lies in maturing industrial applications and making artificialintelligence-based (AI-based) self-learning more explainable, auditable, and transparent, as Greg Satell and Josh Sutton explain in an October 2019 Harvard Business Review article.

Managing information and human interactions is critical to the success of an autonomous enterprise.

The current technology ecosystem gives companies the ability to automate several business processes to complete repetitive tasks. And, as of now, internal processes have been early automation wins in their ability to function without any human intervention and help businesses become more resilient. For example, at TCS, the employee claims approval process is completely automated through an AI-based claims processing solution. Covid-19 lockdowns have expanded the scope of business process resiliency to include contactless operations, borderless workspaces, and remote working.

AI-driven analytics with actionable insights, the intelligent automation of core business processes, and IoT-based digital sensors coupled with hyperscale computing power are various digital capabilities that enterprises will have to focus on as they move toward becoming autonomous. Modern enterprises should continue developing the knowledge and skills they need and adopting intelligent technologies to realize the benefits of autonomy.

“Organizations are trying to take unnecessary costs out of their operations. They’re using technology either to augment labor so that they get more output with the same number of people, or they are replacing manual tasks completely,” says Maureen Fleming at International Data Corp.

At Landmark Group, recent investments have been aimed at automating not only back-office functions, particularly in finance, but also operations in stores, warehouses, and distribution centers, with a focus on sourcing, buying, and managing inventory. The company also has been investing heavily in migrating its entire IT infrastructure to the cloud and automating much of the work done on-premises in its data centers. “Wherever you look at any function, whether it’s finance, supply chain, sourcing and, of course, store operations, everyone in the organization has a plan to automate and improve,” El Fanichi says.

“At the top of the agenda, organizations are trying to take unnecessary costs out of their operations,” summarizes IDC’s Fleming. “They’re using technology either to augment labor so that they get more output with the same number of people, or they are replacing manual tasks completely.”

The wisdom of that approach has been revealed during the pandemic, Fleming says, as many of the companies that have been successful during this time are those that have focused on automation as a core concept. “They have better situational awareness of their inventory,” she says. “They have processes that allow them to provide higher-quality service to their customers. They have agile supply chains. They are more resilient.”

Creating Repeatable Models for Change

Companies making strong progress in the march toward becoming autonomous employ repeatable models that allow them to build on early successes and scale the benefits across the enterprise.

“I like to pick the low-hanging fruit—repetitive processes where we can demonstrate benefits to other stakeholders—and then expand our efforts deeper into the organization,” says Multimatic’s Puvitharan. Multimatic also is experimenting with AI for IT operations, or “AIOps,” tools, which use data analytics, ML, and other AI technologies to identify and resolve common IT issues without human intervention.3

Aon plc, a global professional services firm providing a broad range of risk, retirement, and health solutions, is leveraging AIOps to automate chunks of its IT infrastructure management activities. “Part of our goal is to reduce the amount of noise that comes out of our systems,” explains Rajeev Khanna, Aon’s chief technology officer and senior vice president of information technology platform services. “We’re managing thousands of systems around the world, each one creating alerts when something goes wrong or a threshold has been breached. It can be almost impossible to sort through the hundred thousand or so alerts that come through on any given day.” Today, AIOps handle most of those alerts and allow Aon technicians to focus on the small percentage that really need their attention.

At Eaton, Krishnamurthi looks for the intersection between internal opportunities and evolving technologies—what he calls the “sweet spot”—and then brings the company’s operational leaders and technology experts together to automate processes that can deliver better results for the business. In each instance, those teams are required to make a business case for their project before proceeding. As projects succeed, the company looks for similar opportunities in other parts of the business.

To boost the odds of success, business leaders say it’s important that initiatives be structured as collaborations between the IT function and their organization’s business units.

El Fanichi periodically sends some of his developers, technicians, and system architects into the company’s stores to work with frontline employees and find out how technology might help them do their jobs better. El Fanichi dives in, too. “On weekends, I’ll sometimes sit behind a counter and observe our colleagues as they serve our customers,” he says. “It’s a great source of information and ideas that help shape my view in deploying technology for a better customer and colleague experience.”

This partnership with the business units makes sense for multiple reasons. For starters, it helps achieve buy-in from the business, which is important to winning their acceptance of new ways of doing things. In addition, those on the front lines know best where their pain points are, which can help in prioritizing initiatives. “We in IT don’t always have full visibility into the opportunities available,” says Aon’s Khanna. “We rely on our stakeholders—our business partners—to help us.”


Intelligent Automation in Action

Johnson & Johnson (J&J) is one of the world’s largest and most broadly based health care companies. Across our consumer, pharmaceutical, and medical devices sectors, we are committed to our purpose, which blends heart, science, and ingenuity to profoundly change the trajectory of health for humanity.

J&J established a digital strategy that is focused on three key areas: data science, digital experience, and intelligent automation (IA). As a part of this strategy, IA is a key enabler to deliver on our purpose. Johnson & Johnson’s global services function, in partnership with J&J Technology, is leading the IA strategy for our enterprise globally.

Our objectives are focused on improving business outcomes by reimagining our operating model with IA and driving impact across three E’s:

Experience: Improve experiences for our employees, customers, and suppliers (leveraging our employees for more judgment-based, purpose-driven work)

Effectiveness: Enhance effectiveness (improved business outcomes, agility, improved quality, and compliance)

Efficiency: Increase efficiency to enable improved productivity

IA is unlocking significant value for us by combining end-to-end business process improvements with foundational to more advanced automation solutions, as well as identifying opportunities to completely reimagine how we work.

To drive this strategic capability within J&J, an IA council of senior cross-functional leaders, including supply chain, research and development (R&D), and corporate functions, was established in 2020. They are guided by a north star, which is to excel at IA and be a thought leader in this space by:

  • Inspiring new applications and driving broader adoption of IA to enable focus on more impactful, purpose-driven work
  • Celebrating value creation via successful use of IA across the business
  • Deploying core capabilities that will drive a consistent and agile approach to the planning and execution of IA opportunities across talent, technology, value realization, and change management
  • Measuring and optimizing across the dimensions of installation, maturity (breadth, depth), impact, and adoption

J&J is already leaning into new ways of working and seeing IA significantly contributing to many areas across our functions. For example, in R&D, IA was the key to advancing insights and accelerating informed- based decision making in Covid-19 clinical trials.

Intelligent automation is unlocking significant value for us by combining end-to-end business process improvements with foundational to more advanced automation solutions.

As we envision our future three to five years down the road, we will reimagine our workforce strategy by focusing on implementing virtual workers to handle repetitive tasks while hiring and shifting work to be more judgment-based. Our employees can then apply their time and talents to more fulfilling, engaging, and purpose-driven work, increasing their job satisfaction. Once we reach that point, we will be a truly autonomous enterprise.

“We couldn’t accomplish the size and scale of the work we’re doing automatically without this technology,” says Rajeev Khanna at Aon plc.

Success Stories

Companies leveraging new technologies to drive autonomous operations are scoring impressive wins—reducing process errors, freeing staff to work on higher-value activities, enabling headcount reductions, delivering better customer service, and even driving growth.

Aon, for example, now has 55 processes that have been automated via robotic process automation (RPA), in which software “robots,” typically powered by ML and other forms of AI, do things like opening emails and attachments, logging into applications, copying and pasting data, moving files and folders, and extracting content from documents. All told, the company has automated over the past two years about 700,000 hours of work, which has created capacity for colleagues to take on other, higher-value tasks; reduced error rates; and provided better service to internal and external customers. In its contact centers, the company has leveraged RPA and natural language processing to learn what callers need before passing them on to an appropriate agent in a bid to resolve their issues more quickly.

Now, the company is developing voice analytics capabilities that will allow it to route a caller based in part on what the technology detects about their mood—whether they sound angry or frustrated, for example, or just seem to be looking for information. Elsewhere, Aon has automated the issuance of certificates of insurance to external clients. It also has created a data lake to hold unstructured or raw data from more than 150 million documents, including insurance claims, generated by its business operations—data that couldn’t easily be handled by a traditional data warehouse. It applies advanced data analytics tools to pull insights from that data, which can then be shared with its insurance brokerage clients to help them optimize their performance. “We couldn’t accomplish the size and scale of the work we’re doing automatically without this technology,” Khanna says about the latter undertaking.

Like Aon, Eaton also is leveraging RPA and has automated many processes in its finance, human resources, tax, supply chain, and business operations, Krishnamurthi reports. Late last year, the company went live with a robotic process automation application that automatically tracks warranty repairs, analyzes them for patterns, and forwards that information to product teams to help them with failure analysis and risk mitigation—work that would have required many people if done manually and would have increased the company’s risk exposure. Within IT operations, it’s automated much of the work around responding to service tickets that require changing records within the company’s enterprise resource planning system when individuals join or leave the company or take on new positions, freeing staff for more productive work. Krishnamurthi says the company is seeking further improvements. Just in the finance function this year, the company hopes to automate work equivalent to that performed by 60 full-time employees.

Similarly, automation initiatives at Landmark Group have allowed the company to reduce its IT workforce to about 100 people, down from 550, while providing better service levels. While some people moved on to opportunities outside the group as part of that evolution, others were able to move into new roles within IT doing higher-value work. As an example, in its retail ShoeMart stores, the business has simplified and innovated how the customer is served. A new app lets employees scan the barcode of a displayed shoe to see whether it is available in the customer’s requested size and color, and thereby eliminating unnecessary trips to the back of the store to fetch the shoe. This technology has made employees more productive on the store floor and has allowed them to serve more customers. Overall, says El Fanichi, this automation initiative has enabled frontline retail sales personnel to now spend as much as 50% to 60% of their time with customers, up from about 25% in the past, and has delivered a 30% reduction in customer wait time.


One Retailer’s Journey to Becoming an Autonomous Enterprise

One major North American retailer has leveraged outsourcing and other transformation initiatives over the past 10 years to optimize operational costs. While those initiatives achieved considerable cost savings, the retailer realized it still needed to solve the problem of serving its customers effectively. This problem was due, in part, to the limited intelligence that was not shared, and the siloed approach taken across the retailer’s business processes. Three years ago, the company rebooted its transformation journey to reduce 80% of its technology operations costs while significantly transforming the customer experience to compete better with online retailers like Amazon.

This makeover required the retailer to shift its focus to developing and democratizing enterprise intelligence as a key transformation lever while driving intelligent automation at scale. The company needed to become a so-called autonomous enterprise by using context, intelligence, and automation to drive exponential value. The retailer’s transformation roadmap applied each as part of a five-step approach:

  1. Observe and catalog IT assets and operations to establish transparency and auditability.
  2. Enhance “context-awareness” to establish cross-siloed visibility and a strong data foundation for intelligence.
  3. Intelligently augment people effectiveness to help decide what, when, and why.
  4. Automate tasks and activities to improve productivity.
  5. Make operations “autonomous”: drive exponential benefits by using automation and intelligence to handle situations.

The resilience and efficiency of every business have been tested during the pandemic, and retailers more so than most. This retailer, however, was still able to cater to the demand of essential services effectively while quickly transforming to work-from- home operations as a result of the gains made in the first two years of its transformation plan.

The company needed to become a so-called autonomous enterprise by using context, intelligence, and automation to drive exponential value.

That transformation effort continues to pay rich dividends as it progresses into its next phase. During 2020, while most businesses suffered revenue losses and cost setbacks, the retailer has been able to drive operational savings equivalent to $500 million in revenue growth.

“Becoming an autonomous enterprise is still a faraway dream,” one of the retailer’s executives says. “We are on the right path with a leading agenda. This is a marathon, and we have gained the experience needed to complete it on time.”

“We are tracking our digital maturity in terms of how automated our processes are, and how integrated they are, and how much we are being able to leverage data for decision making,” says Viswanathan Krishnamurthi, vice president of information technology at Eaton Corp.

In addition, the use of radio-frequency identification systems has driven better inventory accuracy across all of Landmark Group’s retail operations, which, in turn, has helped reduce incidents of merchandise being out of stock and also improved the speed of inventory counts. This visibility has ensured better availability of product and allowed for better demand planning, with time and manpower savings for stock counts in stores. As a result of all these developments, the company is now able, for the first time, to accurately expose its inventory for online sales, which has driven a 2.5% to 4% jump in sales. Landmark Group also has purpose built and operates a million-square-foot warehouse that is almost wholly automated, dramatically minimizing the need for human staffing.

As noted earlier, Multimatic has employed AIOps to automate both the monitoring and correction of many of the problems that crop up within its IT infrastructure. “With automated monitoring and self-healing, we are now able to reduce system downtime that can disrupt business operations,” says Puvitharan. “As a result, we now have a much more resilient and stable system and higher productivity in our manufacturing facilities. Automated monitoring and self-healing also have improved productivity within our IT function. For example, checking the health of our entire IT infrastructure used to take above five days. Now it takes about two hours—or less.”


The Most Surprising Thing I’ve Learned about Automation

We asked the automation experts interviewed for this report to identify the most surprising thing they’ve learned about automating business processes over the course of their career. Here’s what they said:

“I’m simply amazed at what can be done. Technology enables people and the human spirit such that we find ways of overcoming any challenge that comes our way. Look at what happened during the Covid-19 pandemic. One day, we were all going to the office and attending meetings, and we believed that without that, we couldn’t work. Overnight, we switched to working from home and having meetings with 15 people on our computer screen—with no drop in productivity.” VIJAY BATHIJA, ETIHAD AVIATION GROUP

“You need to keep a human in the middle. You can’t rely on AI [artificial intelligence] and machine learning models without having a human involved to teach and perhaps most importantly validate the outcome. You can’t just assume the effectiveness of the models.” RAJEEV KHANNA, AON PLC.

“It takes time for people to develop trust in automation technologies. With human beings, we assume they’re doing things right and verify later. With technology, by contrast, we expect everything to work right out of the box and we question its performance aggressively. We’re more forgiving of human beings.” VISWANATHAN KRISHNAMURTHI, EATON CORP.

“The groundswell of interest in automation this year has been an eye-opener for me. It’s become an incredibly important area of innovation. Part of this may be because the interest in driving down costs and the availability of the technology to make it happen are coming together at exactly the same time. It’s a good marriage.” MAUREEN FLEMING, INTERNATIONAL DATA CORP.

“A lot of the resistance to automation is melting away. As people have seen what automation can do, their appetite for it is increasing. I wouldn’t say that’s terribly surprising—most people like things that improve their operations—but it’s been pleasant to see.” RAJEEV KHANNA, AON PLC.

Aon has automated over the past two years about 700,000 hours of work, which has created capacity for colleagues to take on other, higher-value tasks; reduced error rates; and provided better service to internal and external customers.

“We focus on improving the efficiency of a process before we start to create an automation robot. That begins with creating a process map, and then using that map to create a bot that can operate and execute the process on a regular basis,” says Rajeev Khanna at Aon plc.

Overcoming Challenges to Autonomous Operations

Automating business processes, like any big process change, is bound to involve some challenges. Some of the obstacles companies face revolve around technology. IT teams need a solid understanding of the technology options available to them, and data may need to be cleaned before it can be useful in new applications. Organizations also may need to leverage data mining and ML to extract full intelligence from the data they have at hand.

But many of the bigger obstacles pertain to people and culture. Employees, including business unit leaders, may be distrustful of new technology—or worried that it will replace them—and their concerns must be addressed. Employees also may need to learn new skill sets to work effectively with the new tools that are now part of their workflow. Teams pursuing automation initiatives should embrace an experimental mindset that prizes incremental gains and avoids the trap of letting perfect be the enemy of good. And they must share information and collaborate across functions to accelerate the journey toward autonomous operations.

“Organizational change management is critical,” says Krishnamurthi. “Bringing these new technologies into the enterprise impacts the way people work, and in some sense what they’re going to be doing tomorrow. It also can involve a change in culture. It can require a willingness to experiment and to think about technology and data in decision making.”

As with any sort of cultural change, having executive leadership set the right tone at the top is critical. Automation experts offer this additional advice for making these changes as smooth and successful as possible:

Make business users integral to automation initiatives.

“Don’t treat automation as a technology project; treat it as a business project,” says Khanna. “Technology is the differentiator.”

El Fanichi agrees. “There is no point in coming down from the mountain and saying, ‘This is automation.’ I’m the head of technology at Landmark, and I’m acutely aware that it cannot be me leading the charge. It must be the business. As a technology leader my role is to show them the opportunity, but they must adopt it and they must own it. By engaging and collaborating with the business units, you demystify automation. You make it less of a change to be feared and more of an enabler to be embraced.”

In addition to including at least one or two people from the business when forming teams to pursue automation initiatives at Multimatic, Puvitharan says his IT organization does a lot of demos and lunch-and-learn sessions for end users as the initiatives progress, which helps to win their buy-in. Business users become more likely to embrace automation, he adds, when they can see that it will eliminate some of the more repetitive and less stimulating parts of their jobs.

Get manual processes right before trying to automate them.

It doesn’t make sense to duplicate with technology a process that is inefficient, or to embark on an automation initiative without making sure every step of the process is understood and accounted for. “Just because you’re doing something in a particular way today doesn’t mean that’s the way you want to do it tomorrow,” says Khanna. “We focus on improving the efficiency of a process before we start to create an automation robot. That begins with creating a process map, and then using that map to create a bot that can operate and execute the process on a regular basis.”

Process mining can be useful in this effort, adds Fleming. With process mining, data-mining algorithms are applied to IT systems’ event logs to identify trends and patterns that can facilitate the understanding and improvement of business processes.

“Just because you’re doing something in a particular way today doesn’t mean that’s the way you want to do it tomorrow.” - Rajeev Khanna, chief technology officer and senior vice president of information technology platform services, Aon plc.


Contextual Knowledge and Intelligent Automation in Autonomous Operations: Insights from Astellas Pharma Inc. by Shinya Suda, Senior Vice President of Information Systems, Astellas

Astellas is one of the leading pharmaceutical companies in the world and strives to bring a brighter future to patients through innovation.

An “intelligent automation” approach could bring significant value to the enterprise. Rather than having a myopic approach of just reducing full- time equivalent (FTE) count through automation, organizations need to prioritize their automation initiatives to bring in agility, accuracy, and resiliency.

Investing in a comprehensive automation approach amid challenges and during disruptions not only helps the enterprise become resilient, but also helps it accomplish a high quality of output with significantly reduced risk of errors and regulatory issues.

Pharmaceutical companies invest in large operations to deal with the process to intake, analyze, and report safety-related information to relevant stakeholders. These operations need to be extremely resilient under all circumstances, including challenging ones like Covid-19, which has prevented staff from going to offices. Investing in a comprehensive automation approach amid challenges and during disruptions not only helps the enterprise become resilient, but also helps it accomplish a high quality of output with significantly reduced risk of errors and regulatory issues.

Businesses can certainly begin their journey toward becoming autonomous enterprises by automating their simpler operations. However, it is essential that they redesign their business operations to align with intelligent automation to make them independent from their current organizational structures. Employees can then focus more on refining, designing, and optimizing the process and managing the operations rather than executing tasks.

Another area where organizations can leverage intelligent automation is in their IT operations. Regardless of whether they are insourced or outsourced, valuable engineering efforts are spent in monitoring and maintaining the IT infrastructure and applications for 24/7 IT operations. IT is still largely human-centric and there is room for introducing intelligent automation. In today’s digital era, where businesses rely significantly on IT, a tiny outage can cause a huge business disruption. It is critically important for business continuity that IT risks and potential failures be anticipated and proactively remediated before a failure occurs.

Automation can augment human operations, but it takes intelligent automation to make operations smarter and help humans focus on designing, creating, and delivering value for the future by becoming a true autonomous operation.

“Automating parts of your organization requires new skill sets, but that doesn’t mean your current employees can’t be taught those skill sets,” says Mohamed El Fanichi at Landmark Group.

Go for quick wins and scale from there.

“Getting quick wins early is helpful,” says Khanna. “We purposely don’t want to go out and try to boil the ocean. We don’t tell our people we’re going to do 50 things right away. It’s more important that we pick two or three projects, prove the value, and then get buy-in.”

Landmark Group takes a similar approach, says El Fanichi. “When we embarked on our automation journey, we started with small activities—‘Let us generate this report for you automatically, or simplify and automate this heavy manual process’—and slowly but surely brought the organization around to believing in what we were doing.”

Look to automation leaders—and employees— for inspiration and ideas.

“It’s really important to look at organizations making a difference in this area to see what they are doing, understand the technologies they are using, and then do a gap analysis to figure out whether you can use that technology to get the same sort of benefits,” says Fleming.

Etihad Aviation Group is aggressively open to new ideas, whether they’re offered up internally or from outsiders. Visitors to the “innovation” page of its website are greeted with “pitch to us” buttons they can click to submit ideas for improving the airline. Recently, Etihad announced that it plans to partner with Tencent Holdings Ltd., a leading provider of internet services in China, to better engage with customers in China and identify opportunities to provide them with a better customer experience. Internally, Etihad operates an innovation lab that encourages ideas from employees, feeds the best ideas all the way up to the company’s CEO, and offers rewards for ideas that get implemented.

Invest in your workforce to maximize their role in an automated environment.

Inevitably, creating autonomous operations means that some jobs at some organizations will be eliminated. More often, automation experts say, it will mean that jobs are transformed. To avoid displacing workers who may have vast reserves of institutional knowledge, employers will want to give them the tools and resources, including training, needed to thrive in their new environment. “Automating parts of your organization requires new skill sets, but that doesn’t mean your current employees can’t be taught those skill sets,” says El Fanichi.

At Eaton, says Krishnamurthi, the company’s approach has been to help people move on to doing things that are better—more valuable—than what they were doing before parts of their jobs were automated. “We look at automation as a way to augment what people are doing,” he says, “and also a way to better manage future growth and the ordinary attrition that a business experiences among its workforce.”


The company that has no employees may never exist, but we are reaching the point at which it is possible to imagine an autonomous enterprise in which a significant percentage of operations will be handled by smart software and machines— guided, of course, by people who monitor their output and course correct as circumstances change. As has already been demonstrated, even incremental steps toward that goal can yield significant benefits: greater productivity, better customer experiences, faster growth. Companies that ignore automation’s potential risk putting themselves at a competitive disadvantage.

“Automation is no longer a luxury,” says El Fanichi. “Automation in our frontline processes or in our core back- end operations has unlocked massive efficiencies within our organization. It is an absolute must to continue finding cost reductions, unlock the potential tied up in non-value activities, and maintain our competitive advantage in our market. Automation’s impact is real, and either you get on the boat or you drown. It’s a matter of survival.”


1. McKinsey & Company, “Why Productivity Growth is Slowing Down in Advanced Economies,” February 20, 2018. insights/regions-in-focus/solving-the-productivity-puzzle/pt-br.

2. Unit4, “Office Workers Lose a Third of Their Work Time to Admin According to Independent Research,” citing survey by DHS Research, April/May 2017. research.

3. Rouse, Margaret, “AIOps (Artificial Intelligence for IT Operations),”, TechTarget, May 2019. https://searchitoperations.techtarget. com/definition/AIOps.


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