The 4th industrial revolution has created buzz words such as ‘the future of work, artificial intelligence (AI), robotics, and digital revolution,' which are on the lips of many in the HR community.
‘HR disruption in the digital era’ is a typical theme for a conference keynote address, and trade magazines scream headlines of the shape of work to come. What appears to be less evident is a deeper understanding of the organisational implications this new wave of technology will have on the workplace, particularly during implementation.
Artificial Intelligence has already made its way into many workplaces. In a global survey conducted by Infosys in 2018, 57 percent of Australian large businesses (with over 500 employees and $500 million revenue) had deployed some form of AI, typically to improve existing processes through automation and estimates have put AI increasing global GDP by $15.7 trillion in the next 12 years.
So, when it comes to managing an organisational change such as the introduction of AI technology – albeit a more sophisticated tech type that can make decisions and perform tasks without explicit instructions from humans - is it safe to assume that we treat it just like any other implementation of any other system? Not quite.
For sustainable success, and to maximise the financial and societal benefits that are predicted by fully implementing AI workplace capabilities, consider the following factors in your change strategy.
Is your organisational infrastructure supportive enough for AI? Be prepared to review, re-design and then implement change in up to three areas: work design, business process and business models.
A formal organisational infrastructure that has tight control over processes and employees needs to give way to a more adaptable one, where communication is much more open, employees are empowered to make decisions, and team structures are fluid.
Why? Depending on the solution being put in place, agility and collaboration across functional business units may be needed to react to insights gleaned from AI machine analysis, whilst also being able to leverage such findings in business problem solving and go-to-market strategies. Companies that will do best are those that are agile and can respond quickly to AI opportunities with both an experimentation and learning lens. Organisations need to be able to be nimble enough to move to the new environments required, and change capability and maturity is required from all levels to successfully implement such adjustments.
Are leaders skilled to maximise the opportunities from AI?
Business process and business model redesign can be done well when looking at it from the customer or user’s viewpoint, and as a result, requires leaders to demonstrate design thinking skills. Before fully adopting processes and scaling them up through the organisation, embracing and promoting experimentation to look outside the square and explore AI potential will reap the best benefits.
AI can’t be effectively implemented by leaders who simply search for processes that need automating. Instead, it requires business analysis into areas where human and machine integration and augmentation can occur.
Such thinking requires innovators who can envisage a very different workplace, and then have the change leadership capabilities to put them in place. This is when intellectual intelligence (IQ) needs to move to the side and make way for emotional intelligence (EQ). How well are leaders equipped to paint a compelling vision for the workplace of the future? Will employees see ongoing authentic leadership communication, honesty, and the inclusivity they need to join the journey?
Does the workforce trust the technology you’re implementing?
Even though the consensus is that there is no intention to displace employees with AI robots and machines, the transition to be an artificial intelligence savvy business starts with trust in the technology and its role in the workplace. A 2020 survey conducted by KPMG and the University of Queensland found that a central element to the adoption of AI is trust, and currently, only one-third of Australians are willing to trust the output of AI systems. Much of this suspicion is born out of a lack of understanding and awareness of AI and its use, and this distrust doesn’t discriminate at hierarchical levels. For executives who spend significant time on report and data analysis to help inform decision making – which could be automated by AI – the lack of AI-led decision transparency causes concern because they feel they have less control over the end result. For employees whose roles are augmented by machines, the leap of faith required to assist machines, to be assisted by machines or both is great. New skills come into focus – many not straightforward to educate - including questioning, collaborating, judgement and creativity, and sufficient notice and retraining is required and expected.
In summary, in an age where machines will leave humans to leverage their ‘soft skills’ both on the front line and in leadership, a more emotionally intelligent individual, will operate in a more collaborative and dynamic organisation, where respect can be harnessed, and decisions can be made at all levels of the hierarchy. This is no ordinary technology implementation, and careful management of the people side of this type of change is more critical than ever.