In 2022, we’ll see the realization of the impact of the “Power of Two”, where enterprises reach their full potential through a unified workforce of human and digital. We’ve moved past the fear paradigm of seeing digital labor as a risk and, instead, see it as a means of unlocking our full potential.

The opportunity to help bring about the next evolution of workforce transformation, just like the BPO (business process outsourcing) wave did back in the 90’s and 2000’s. Lessons learned by organizations using offshoring and outsourcing for more than just labor arbitrage can be leveraged again with their use of silicon-based workers in a strategic workforce way vs small tactical ways.

Employee onboarding and offboarding are the immediate automation requirements, especially considering that most HR departments are experiencing similar levels of churn, exacerbating the situation. Beyond that, IA helps decrease the amount of training required for new hires

Focus not on the products but on the work that needs to be accomplished. Recognize who in the organization really has process understanding and finally, look to the future of the maintainability of the automation.

It’s hard to pick a single industry since many of the core processes intelligent automation can assist with are, in fact, cross-industry, such as quote to cash, HR, financial reconciliation, etc. Of the industries where gain can undoubtedly be made, utilities, health and government are exciting areas where you can see, not just singular companies or organizational units being able to make huge gains using IA, but collaborations across different organizations using common Digital Exchanges (DX), such as within the NHS, UK.

Hybrid working has already driven a change in how digital workers are used and how automation can be beneficial to hybrid working. The impact will be a greater focus on interaction between human and digital workers. It will place a greater significance on “human-like” traits of the digital worker – for example, a greater reliance on natural language understanding (NLU).

Digital labor means than enterprises can reimagine the way they deliver existing or new products or services. When considering how to take a new product or service to market, doing so with digital labor provides a far reduced cost approach while allowing for the approach to be standardized. In the case of sustainability, in-region/in-language services can be offered without the carbon footprint, and offerings can be more easily trailed without the investment leading to a lower business burden.

The question of ethics moves well beyond AI, IA and PI (process intelligence). The reality is, the question needs to be considered around two aspects. Firstly, what systems are being used for. We have all seen the realities of utilization of technology for social engineering that was exposed previously. It would be naïve to think this will not happen again or indeed is not happening at present. We do, though, need to have strong regulation around how citizen data is utilized by corporations and political organizations. Furthermore, Draconian consequences should be in place for breaching such regulations; consequences that go well beyond fining offenders the amount of money that is potentially rounding errors in relation to the gain they make. Secondly, human rights over data. It is apparent that the right to own your data and direct who has it, for what it is and is not used, is quickly becoming something that needs to be enshrined within our human rights codicils. Without this ability for the individual to control their own data, abuse of such will go completely unchecked.

I predict that a number of high-profile stories about the rise of power of AI and the weaponization of robots will have a detrimental impact on human opinion, and the view that they are coming after our jobs will continue to expand.

Focus not on the products but on the work that needs to be accomplished. Recognize who in the organization really has process understanding and finally, look to the future of the maintainability of the automation.

Access to more intelligent decisioning technologies will increase the capabilities of robots to address nondeterministic or predictive problems. Self-healing will begin to be established as a way for robots to adapt to changing environments and applications. Access across a broader range of technologies and more complex processes will introduce more of a collaborative dynamic to the robotic landscape (meaning, collaboration between different digital workers, and humans).

Processes begin and end with people. The recognition that you need a symbiotic relationship between digital and human labor is one that is reinvigorating and changing the perception of automation — from one that brought fear to a more positive outlook, where automation is an enabler for positive change (for example, the move to hybrid/remote working, which would have been impossible without automation).

The applicability of digital workers continues to grow due to the rapid increase in their capability. The trend of embedding AI and ML as ‘skills’ available to the digital workers will continue at pace, unlocking new scenarios where they can add value to the enterprises that adopt them.

Be courageous and prepare to adapt as you go. Automation is not a three to five year, tens of millions program of change. It can be fast-paced and quick to deliver value, but courage is needed, as is leadership, to set the vision and to pursue your goals.