The rise of information technology and artificial intelligence is bringing a new age to the workplace: that of intelligent automation, which we believe will enable employees to achieve significant productivity gains—as much as 30-40%—even in functions that are already automated.
Of course, many of the key elements of intelligent automation have been around for some time. Robotic process automation, for instance, has long enabled enterprises to offload repetitive, rule-based tasks to machines, delivering dramatic improvements in accuracy, cycle time and increased productivity in transaction processing while elevating the nature of the work performed by humans.
Now, analytics and artificial intelligence are breathing new life into automation technology. Through new modes of human and machine collaboration, these technologies are doing much more than just eliminating repetitive tasks; they are supporting humans in complex and creative problem-solving by enabling analysis of dauntingly vast amounts of data and identification of trends previously impossible to detect. And, machines will increasingly be able to interact naturally with their environment, people and data by “learning” from a body of knowledge without coding all business rules manually. By introducing intelligent systems that can truly mimic and augment human behaviours, and do it hundreds of times faster, these technologies make both humans and machines more powerful than they can be on their own. Intelligent automation is clearly a game-changer when it comes to improving complex problem solving, risk analysis and business decision-making.
Many business leaders today know they want intelligent automation, but may not be ready to answer some of the key questions to move forward. When is the time right to invest? What are the right investments for my business? Can I entrust machines with critical business processes?
Three lessons learned
While implementing intelligent automation has the potential to be a disruptive process, organisations need not get bogged down by its seeming complexity. To realise intelligent automation’s potential and reap its benefits, organisations can start by understanding three lessons Accenture has learned:
First and foremost it’s about people: Often organisations focus too much on cost reduction or eliminating repetitive tasks and not improving judgement-based tasks that enable people to do new things. Think of machines and artificial intelligence as the newest recruits to your workforce, bringing new skills to help humans do new jobs, and reinventing what’s possible. It’s about the primacy of people—consumers, employees and ecosystem partners accomplishing more with their digital co-workers.
Get the basics right: Artificial intelligence needs data to be trained to be effective in a particular business
domain. This means companies need a data strategy in place and a reliable, scalable data store. There are also security concerns whenever automated tools are accessing the system—new security vectors; responsibility for consumer privacy; demand for transparent use of data.
And finally, not all processes should be automated. Some may need to be streamlined first, or eliminated altogether. New processes may need to be developed. Within Accenture, we recently introduced a comprehensive program to infuse automation into our client service delivery. As a first step, we recognised the need to reduce, eliminate, and overhaul before we started to apply intelligent automation at scale.
Embrace open innovation: To be effective, intelligent automation can’t be applied in isolation, leveraging just one tool or one capability; rather, it must be paired with multiple key technologies, even some “mundane” ones, and integrated with back-office or external systems to serve a specific business function.
Adopting intelligent automation is one way companies can master the four pillars of digital corporate culture.
Become built for change: Today, organisations must be built for change, which may mean changing how they operate as a company. Automation plays a very big role in making software, and by extension business, built for change.
Become data-driven: Companies will need intelligent automation embedded into the fabric of their business in order to make data-based decision-making so pervasive that people and machines alike are equipped to harvest and act upon it.
Be digitally risk-aware: This means facing and factoring in newer risks that traditional businesses were never exposed to: security, consumer privacy, data transparency and responsible use of technology—which are growing in volume and complexity.
Embrace disruption: Intelligent automation changes the rules by innovating with new products and services on a scale previously infeasible. Disruption will be inevitable. But rather than be a hindrance, this disruption should be seen as an opportunity—to rethink what you do, and how you do it, across every area of your enterprise.
Of course, this all depends on the successful implementation of intelligent automation—which requires an approach that is people-first, business-oriented and technology-rich. When followed, these three principles will enable companies to integrate intelligent systems effectively, thereby improving operations. Companies that think beyond costs, with a people-first mindset, will be best positioned to drive this change.
By Bhaskar Ghosh
The writer is group chief executive, Accenture Technology Services