Tuomas Syrjänen, co-founder AI Renewal at digital innovation consultancy Futurice, and Eeva Raita, Futurice head of culture advisory, explore five ways in which AI and machine learning will reshape cultural paradigms in the workplace
Despite AI finding its way into all areas of our lives - from recommending what we watch, to tracking our spending - when it comes to businesses embracing the AI enabled workplace, there’s a long way to go. A recent Microsoft report found that half of UK companies have no AI strategy in place and fewer than half of staff surveyed trust their organisations to use AI responsibly.
From our discussions with business leaders, there is a widespread failure to grasp the seismic shift between the linear business processes of the past and how AI will transform how we work. Here are five ways in which AI will reshape cultural paradigms in the workplace:
1. Probabilities will trump planning/strategy
Faced with uncertainty, such as the arrival of new, more agile competitors, businesses typically react by developing a centralised strategy to tackle the threat. In an AI-driven world it is possible to build a digital ‘proxy’ of different scenarios. When combined with experimentation, AI proxy scenarios allow leaders to test aspects of their strategy and gain a more accurate idea of how alternative options could pan out. 'This suggests a greater role for AI will open up in areas such as project management where by combining data from previous projects with real-time information such as weather reports or site logs, it will be possible to forecast scheduling or project overruns more accurately - useful in construction.
What does this shift mean for business leaders? Companies that have traditionally relied on strict targets, detailed plans and a cautious, incremental approach to change, will need a more flexible outlook. In an AI-powered world, the emphasis will need to be on observation, iteration, prediction and continuous learning.
2. Decisions will be data-driven
Data and AI are set to drive a new approach to decisions in which data-driven facts will supersede internal politics or the CEO’s gut instinct. This shift to data-driven decisions will put pressure on the quality of data a company has. The more effort businesses put into generating quality data from a wide range of sources, the more likely it is they can achieve a transformational outcome – across areas including improved shipment logistics, fraud detection and greater tax efficiency. Even something as simple as ‘data cleaning’ can have a big impact on the bottom line (as GE discovered when it used machine learning technology to help clean and integrate supplier data across business units, saving it $80m).
What does this mean for business leaders? Data can help businesses make better decisions - but only if business leaders are prepared to put aside their egos in favour of the facts. Data-driven decision making also requires companies to develop a robust data infrastructure to ensure data is good quality and has been cleansed, correlated, linked and is machine-readable.
3. Knowledge within businesses will be visible immediately
McKinsey recently estimated that employees spend 20% of their working week searching for information or for colleagues to help with tasks. Meanwhile Lew Platt the former Hewlett Packard CEO, famously remarked, “If HP only knew what it knows we’d be three times more productive.” Challenges related to knowledge management are especially acute in larger companies and businesses that rely on autonomous teams and remote workers. In these contexts, efforts are duplicated and lessons aren’t learned because there is no fast, easy way to surface and retain people’s knowledge and expertise. AI-enabled search engines can transform knowledge management by extracting data from company intranets, shared calendars and chat platforms like Slack, immediately highlighting team members’ areas of expertise. The competencies and knowledge of an entire workforce can be visible in seconds rather than hours or weeks. Meanwhile, on a macro level, a company’s productivity and scalability are less dependent on headcount and driven more by accumulated expertise.
What does this mean for business leaders? Faster and more efficient knowledge management will allow companies to react to challenges and opportunities much more quickly. That said, knowledge on its own is just raw data: to have any value, it needs to be converted into insights and applied intelligently to support a company’s goals. So, the key message is: knowledge and data are not the new oil, better insights are.
4. Teamwork will be AI coordinated
With the integration of AI it will become possible to design high-performing teams on the basis of data. By pooling peoples’ Myers Briggs profiles, their personnel records and stated personal ambitions, AI can assemble the best team for a particular project based on their skill sets, personalities and working styles.
AI will also help teams become self-organising, for example deploying chat bots to coach teams through difficult problems they encounter on the way and by helping them to quickly understand the bigger picture around what their small team is working on. It can also prompt additions and improvements to the team along the way.
What does this mean for business leaders? Human-machine collaboration requires a radical rethink of role definitions, success measures and career progress. The best decisions will come from people working alongside machines, with AI optimising not replacing teams.
5. Automation will rule
A major impact of AI will be automation – allowing companies to streamline mundane, time consuming jobs such as processing invoices, managing records, inputting data. With AI, tasks could be transformed via automated fetch of data or mass generation of tags for data. Greater automation has cost efficiency benefits, however if its implementation is not handled sensitively, it could potentially create pushback from people either worried about being replaced by AI or unwilling to relinquish budget or control.
What does this mean for business leaders? AI requires the C-Suite to rethink the way they incentivise employees and to embrace a culture of continuous learning – where diktats to beat targets are scrapped in favour of mantras such as ‘learn, unlearn, relearn’. Employees need to be convinced that an AI future is one where they will be freed up and supported to become creative problem solvers rather than finding their skills and expertise superseded by technology.
AI has the potential to be transformational - Microsoft found that organisations already on the AI journey are outperforming other organisations by 5% on productivity, performance and business outcomes. Achieving this step change requires leaders to perform a cultural reset which prioritises a culture of continuous learning, in which data drives strategy and investment and where customer and staff wellbeing are front and centre of the company’s mission and purpose.