In the early 2000s I worked for a manager who, amongst other great traits, was honest about workload and time; if I had achieved all I needed to that day, week, month etc, I could leave – I just had to take my phone in case I was needed.   

My manager understood the difference between Time and Impact.   

Over the years there have been books written on this subject, and I have met individuals with a similar mindset, who lead high-performance teams. This method of working can be very productive, but it requires trust between employer and employee. The old command and control methods of running teams is no longer applicable with this management method; individuals must be given the freedom to achieve and to deliver on the expectations set upon them.  

This this will ultimately lead to the optimal adoption of AI, as users will focus on the outcome they want to achieve and how they can best adopt and implement AI to achieve this. 

Table Of Contents

• Re-thinking productivity with AI’s capabilities 
• Trust is the cornerstone of successful AI implementation 
• Impactful and value-add AI creates time 
• CDW and AI 

Re-thinking productivity with AI’s capabilities 

Growing up, my first jobs were customer-facing, meaning there was a time range where you had to be present; you started at a given time, had breaks in shifts and finished at a set time. All of this was designed to match the opening times of the shops I worked in.  

This was an easy metric to measure my performance against. I was present and on time, or I wasn’t.  The way we work hasn’t moved on for some time - yes, we still see opening hours for customer-facing businesses, but there are out-of-hours options for customers and multiple ways to interact. If you have a day of back-to-back online meetings, has your day been productive because you have been busy all day? Usually, I find this is not the case. Busy doesn’t always equal productive.  

Working 8 hours is, invariably, not a good measurement of productivity.  Over the last few years, I have had a lot of conversations with businesses about changing the metric for performance from ‘time present’ to ‘impact’. Albeit potentially subjective in nature, it is a truer measurement of an individual’s output. 

So, how does AI factor into this conversation and how does it drive productivity?  

The biggest value AI will deliver to you, and where it will have its greatest impact, is time. The correct utilisation and implementation of AI will remove the mundane, freeing you to focus on the important. By having AI analyse data you can make more efficient decisions in less time, and by always having access to AI, you can support users or customers at times when others may not be present. 

There will be time required to implement, train, and introduce AI, but just like the first computers that offloaded computational tasks for humans, the next evolution of AI will take this to the next level. 

Introducing AI will also come with design, implementation, training and operational costs. These are easy to calculate, but what is the return on investment? 

At CDW, when considering the implementation of AI, our first step is to align an AI strategy to your business goals, which will support and generate a return on investment. 

Questions you could expect to hear are: 

• What AI capabilities exist and how do they support the business? 
• What are your existing strategies and goals? 
• Where in your business will the introduction of AI realise value the quickest? 
• Which AI implementations will give the maximum amount of time back to your business? 
• How mature is your current data strategy? 

Ultimately, through the delivery of AI, you will create your own metrics of success as there is no ‘one size fits all’; but there are some simple concepts you need to understand and adopt. 

Trust is the cornerstone of successful AI implementation 

During the pandemic I wrote an article on trust and how this is the cornerstone for those working at home, both for the managers to understand how the workers were operating while out of sight, and for the employees to rely on their managers to support them even when all of their actions, presence and hard work may not be immediately visible.  

Trust has always been the cornerstone of any good relationship. It is also now imperative that an AI application introduced to an organisation is reliable and accurate enough to develop trust, both in how it handles data and the results it generates. 

A badly implemented AI strategy could cause more harm than good. Understanding ‘why’ will help you gauge the potential value and the return you can anticipate from this investment. Any business looking to invest in a new technology wants to be sure of its return on this investment; with AI the opportunity to spend a lot of money developing a solution that is not going to deliver on this return is a very real possibility.  

Impactful and value-add AI creates time 

If I were to recommend one metric that could be used to accurately deliver value, as I mentioned earlier, it would be time - time that has been made available to your most valuable resource: your staff.  

Productivity, innovation and creativity are all difficult to measure (in a non-manufacturing scenario), however, they are the result of time being made available to individuals to demonstrate these capabilities.  

How will your implementation of AI create time, and how much time will you consume in its creation? 

CDW and AI 

There is a good chance you are considering AI in one way or another, even if it is to just ensure your data is protected. CDW can help you understand the opportunities, AI types, learning models, infrastructure, security measures and the entire end-to-end solution that is AI. With a simple engagement we can help you look at the first steps of AI choice and alignment, as well as briefly looking at business readiness, to help you understand what AI could mean to you and your business.  

This is the last in a 4-part blog series written by Tim Russell, the Chief Technologist for Modern Workspace at CDW UK. Subscribe to updates at  

Other blogs in this series: 

• AI in the Workspace - Part 1: AI – Disruptor or Innovator? 
• AI in the Workspace - Part 2: AI – A Business Dilemma 
• AI in the Workspace - Part 3: Adoption Challenges of AI 
• AI in the Workspace - Part 4: Measuring AI’s Value and Impact