The business landscape is changing due to AI. Estimates by McKinsey show that AI will add $13 trillion to the global economy over the next decade.
But it doesn’t feel like we are ‘there’ yet. Further research by McKinsey showed that only 8% of companies core practices support AI adoption. The majority of companies that have utilised AI are only running pilots or applying it in a single business process.
Why have companies been slow to embrace AI?
Aside from technical requirements (e.g. consuming the right data and producing the right decisions/insights), AI needs two things to add value to an organisation.
It needs to be aligned with the meaningful mission of your company (which should be more than just profit) and needs to inspire change and behaviour in people.
Sanders states “While financial performance and shareholder value will always be important, creating human-centered, technology-powered organizations will actually drive financial performance in the age of AI.”
Many organisation are harnessing AI just for the sake of tech, or worse — to the detriment of their organisation. Looking at Facebook, for example, it was shown that their use of AI actually conflicted with their mission to connect people and bring the world closer together.
Another common story of failed AI goes like this: A company works with an exciting technology provider and invests time, money and resource to create a proof of concept. Everything is going very well (in the IT team) until it comes to changing business processes across the organisation to adopt AI. The technology is there, but the willingness isn’t there from senior management to drive change and make fundamental shifts in the way decisions are made and processes operate throughout the organisation.
Companies can pour as much time and money as they’d like into developing the best AI possible, but initiatives will fail without both technical and social systems integration.
This leads to the reality that humans and AI need to be fully integrated for AI to be a true success. AI should support human decision making and not replace it.
Consider this example from medicine — research in the journal of Nature found that “good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone.” This shows bold decision making that requires a high degree of human skill and knowledge can benefit from AI, so long as it is integrated properly and fully within the context and process that the person is in to make a decision.
Staff should learn how these algorithms and their outputs can make their jobs easier, and allow them to perform better (and not to be replaced by AI).
Senior management needs to communicate the AI vision clearly — including showing and demonstrating what ‘good’ looks like throughout the AI roadmap.
Orderly and AI
AI-generated scorecards such as those offered by Orderly have been used to influence human behaviour for good across the food and beverage supply chain. In an effort to reduce waste and increase sustainability, the scorecard concept works with a number of data sources to provide the user with easy to understand overviews:
● 3 things they are doing well to increase sustainability in their organization area
● 2 things they can improve upon
● 1 score out of 5
The score enables them to track their progress over time and benchmark themselves against their peers.
Each week the scorecard is updated with new recommendations and the system checks the data to see if recommendations have been followed by the user (self-learning).
The idea is that if each person in an organization has a scorecard and makes the two small recommended changes to their behaviour each week, the benefits multiply and indeed continue to do so as more people use the scorecard.
Orderly also deploy forecasting solutions at major enterprises to assist with demand and risk planning.
Interesting in hearing more? Contact us today.