BUSINESS STRATEGY
has the power to really mess things up , and that is the path too many businesses are blundering down today .
MAJOR DECISIONS ON IMPLEMENTING AI ARE MADE AT THE TOP BY THE SENIOR TEAM AND ARE TOO OFTEN BASED ON OVER-OPTIMISTIC , UNSUBSTANTIATED BUSINESS CASES THAT WISHFULLY PROMISE GREATER PRODUCTIVITY AT SIGNIFICANTLY LOWER COST .
For those who were around in the noughties , AI is history repeating itself as there are strong parallels to implementations of ERP systems circa 20 years ago ( oversold benefits , lack of relevant education and problems from automating poor processes ). But this time the pressure is even greater due to the higher costs of AI solutions which promise to deliver even higher productivity gains , but within unrealistic timeframes .
AI embedded in HR systems are a particular example – many places need to simply turn them off ! Inherent biases in existing working and hiring practices can be magnified using AI-driven systems , already causing numerous problems that have been successfully challenged in court for discriminatory hiring and staff promotion practices . Also , are we in danger of bringing back the 10 % promoted and 10 % cut approach , all based on AI-driven quantitative not qualitative data infused with bias ?
Other examples include AI demand-planning software . Putting aside that these have the
( critical if you are to understand why something is being recommended ).
As for AI ’ s dehumanising impact on customer service , hands-up anyone who looks forward to first navigating the AI chatbot before they can deal with a human . Enough said ! A number of household names which invested in deploying AI in real-world customer service roles , such as taking orders at drive-thrus , are already scaling back based on unsuccessful trials revealing the inevitable problems that come when an emerging technology has to deal with the foibles of humans . More businesses should follow suit !
AI is proving bad for customer relationships as businesses , once you remove the flowery justifications and hype , are generally using it to reduce cost and replace experienced people , rather than deliver a palpable improvement for the customer .
Not only is AI too often dehumanising customer service , it is also bringing tension and burnout to employees . Particular problems include :
1 . Middle management burnout from devising and deploying AI . With AI implementation programmes , we have teams being given little or no training and expected to deliver a major change programme , underpinned by potentially unrealistic project and operational expectations from senior management . Given the high cost and complexity that comes with implementing a new technology , it is a recipe for failure .
2 . Employee burnout from dealing with the problems when the productivity gains fail to appear . As with previous technology implementations ( e . g . ERP ) people are not being given the skills and training to properly implement the changes and then have to deal with the consequences of the change programme ’ s poor implementation and performance . We are seeing a backlash from employees against the drive for productivity : not only are affected employees feeling less-and-less valued , but they also recognise that often they are now competing against the AI engine , giving them unachievable targets to hit .
inherent shortcomings of simply being a more sophisticated version of driving the business using a rearview mirror , they spit out a number without any insight on the algorithms and embedded logic that led to the predictions
3 . Customer service deterioration . We are seeing companies race to implement AI without sufficient consideration for how it will help differentiate them in the marketplace , and then fail to provide the necessary training and change management support to their staff , so customer service levels and ultimately profitability drop while your best staff leave . The perfect doom-loop ?
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