Executive Leaders' Role in Guiding Responsible Automation Strategies

Automation is everywhere around us, and within businesses, leaders have a shared responsibility to ensure that automation and its technology are adopted seamlessly. The ethics of AI have been questioned heavily, especially recently when it’s become more prevalent across industries. We’re going to unpack responsible automation strategies that leaders can use for their teams.

How can you make automation strategies responsible? 

Deloitte recently produced a compelling guide on this, which highlights ideas that can be adopted within an organisation. The bottom line is that AI ethics demand attention, and they must be aligned with corporate values as well as accepted by the individuals who will be using them. 

Step 1: Plan for reskilling

“Take a future-focused approach to reskilling, planning out what roles might be impacted based on strategic objectives and therefore where development may be required.”

It’s no secret that AI and automation are going to change how your workforce operates. However, instead of allowing minds to run wild and fear to creep in (which is a natural feeling for a lot of employees who think their jobs will be impacted) focus on reskilling. 

Planning in advance and understanding which departments and individuals need to be upskilled will enable you to create personalised development plans for each employee. Not only will this generate trust and value, but it’ll also allow for the automation you’ve implemented to make a real impact. 

Step 2: Educate the workforce and encourage a mindset of learning

“Create a culture of continuous learning at all stages of the employee lifecycle from attraction to exit. Find ways to reward reskilling.” 

Alongside reskilling, you must also embed a culture of learning within your organisation. This can be very difficult in the early stages of change and transformation, especially if your organisation is just starting to implement automation. It can be difficult to adjust to and you may find that there’s a lot of resistance. 

However, focussing on reskilling (as previously mentioned) and creating continuous learning opportunities will make change much more palatable for employees as time progresses.

Step 3: Gather feedback and use a feedback loop to ensure that communication is prioritised

“Ensure transparent communication even when you don’t know all the answers.”

Communication is key! And, the only way to instil better communication is through gathering continuous feedback. 

We recommend using a feedback loop, which is defined as A feedback loop is a process that “loops” the outputs of a system back in as inputs. In business, this means using customer or employee feedback to improve a product, service, or workplace: a business uses the insights gained from feedback to initiate change [source]. 

A breakdown in communication (or lack of it) is what causes resistance to change and transformation, or worse - the transformation to be unsuccessful as a by-product of this. If you’re able to use the above three points as a foundation for guiding your automation strategy, then you should have a positive outcome. It’s important to create a system that works for your organisation, too. 

Why talent attraction and retention is crucial during this period

In essence, guiding responsible automation strategies falls under digital transformation and technology adoption. We’ve spoken previously about the importance of hiring and retaining high-quality talent to lead change, so keeping this front of mind is crucial. 

Retaining talent who have successfully implemented and adopted AI technology does not just safeguard your future workforce from having to re-skill and relearn if that individual has left. It also creates a culture that is rooted in accepting AI and having a positive experience with it. 

Unfortunately, many organisations lose great talent due to poor transformation techniques, which leaves employees feeling fatigued and unheard. They then have to re-hire and re-skill whilst running a transformation simultaneously, which is incredibly challenging and often extends the length of the transformation as a by-product. 

Criticisms of AI and how it distorts the human experience

Although AI has positively impacted many industries, there are still a ton of criticisms of AI and how it distorts the human experience in particular. Let’s look back to a world before technology. Life was harder in many ways, but it was also a lot simpler. 

We didn’t have AI algorithms pushing content through our TikTok to keep us addicted to our phones for longer. We didn’t have access to endless, almost incomprehensible information across social media that has been proven to cause mental health issues. The human experience, arguably - should be simple and be driven by choice.

However, AI and other technologies almost take these choices away from us as our behaviours are predicted by data that we’ve willingly (or unknowingly) given to the platforms that we use on a day-to-day basis. This allows our human experience to then become manipulated. Read more about our findings on this here.

Deloitte has produced an extensive guide which has supported the production of this article. You can read the full guide here.