What value can you expect from AI

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Developing a robust AI strategy is paramount as businesses increasingly use AI technologies to drive innovation and efficiency. Beyond the technical intricacies of AI implementation, organisations must navigate a complex landscape to identify where true value lies. This value goes beyond merely adopting AI tools; it requires a strategic approach that aligns AI initiatives with broader business objectives and addresses the nuanced challenges of adoption and benefit realisation. 


Within this strategic framework, the quest for efficiency and productivity is undeniable. Managers seek to optimise workflows and streamline processes, while workers eagerly embrace AI tools like Microsoft Copilot to enhance the value of their time. However, the accurate measure of success in AI implementation lies not solely in technical prowess but in unlocking tangible benefits across multiple organisation dimensions. 


When we deliver AI strategy information to our clients, we find a range of interests or capabilities across these areas. Organisations understand that they can save time; however, that needs to build up into more tangible benefits, such as reducing the cost of delivering that capability or linking that capability to increased revenue, customer satisfaction, and brand uplift.   


As information workers, we include the benefits of time saved and the promise of more accurate results in our collective job descriptions.


One exciting trend appears when we look behind the AI tools and into the adoption and benefit realisation aspects of the AI Strategy.  Identifying or measuring who is benefiting from an AI-enabled activity can be challenging. 

 Let’s look at some examples of what I mean: 

Having AI do our emails:

  • The idea of productivity from not having to spend time in our inbox is like ground zero for the “AI for everybody wins” conversation.  When people who have worked in trials see an email, they can read it and decide their response almost instantly.  However, the anxiety over phrasing, content and other aspects can overwhelm.  At this moment, AI swoops in, “I have all the words!” what a match.  However, there is a moment when the user must hand their words and intent over to the AI – they need to follow the AI’s approach.  A process that may take 10 minutes (we don’t know because we’re not watching the clock) will take 8.5 minutes using AI, but it feels different because they’re working with someone else’s approach or the mental strain of moving past the blinking cursor is avoided.  The other aspect to consider is – will the recipient know that an email has been crafted using AI and treat the message differently (subconsciously or otherwise).  Does a value exchange happen here?  Understanding this means we can look for more comprehensive approaches in change management, tool selection and expectation management.   

Having AI execute the tasks as an assistant:

  • AI investment is incredible in this space, and many vendors are throwing enormous resources to help unlock this problem, from AI-enabling RPA to Desktop embedding and planning software.  All are designed to take tasks away and turn them into meaningful time for our best and brightest.  And yet, RPA is fragile – suitable for a solid set of outcomes but not in industries where change and growth are constant.  You would expect desktop activities to be owned by the major players eventually (Microsoft, Google, Adobe, OpenAI and Amazon are here and now, and they’re spending big.  It is unlikely that they will not consume the most common activities in time), so do you invest now or do you plan for what’s coming instead?  And ultimately do these task-based actions ultimate lead companies to take the time and invest it in their people so they can grow?  Or do they add more tasks?  The truth is somewhere in between.  The organisation that thinks ahead and demonstrates value in their people and consideration in their task reduction will likely become the employer of choice in a productivity-enabled workplace. 

Our AI understanding and the elements we focus on in strategic discussions are not just bound by what is possible but also by thinking about where the value comes from.  This way, we can look for broader results than just “automating a task”. We look to articulate and confirm the value of task automation from four different perspectives: 

  • The impact on the person performing the task—does the time saved equate to the anticipated benefit of higher productivity? 
  • The impact on the task itself – is the task, now performed by AI, adding to revenue or reducing the cost of service delivery? 
  • The impact on the downstream processes and people that follow (internal and external): Has customer satisfaction improved, and is the business performing better overall? 
  • Where is the client’s market heading?  Are these the issues to worry about, or is there more value behind the horizon of adoption?  Has the business now protected itself from disruption (or begun a disruption of its competitors)? 

We focus on these aspects to ensure each element realises the immersive experience and value the AI promise describes within the client’s context.   

Our thought process involves educating the market on AI to speed up and improve collaboration.  So much of the current discussion is about individual results – a task here, an email there, or a new agent on the desktop that interacts with the person – however, it all comes back to value.  There is still so much to explore, but I wonder whether the pandemic hype focuses on the right things that will truly differentiate.  We will continue to look at improving the commonly accepted items available today, helping businesses innovate beyond their current business and technical architectures, and looking at new operating models. 

We would love to connect and help you formulate your next step.