There has been incredible hype around artificial intelligence, machine learning and intelligent automation.

The emerging technology has been presented as both a threat and the source of opportunity – particularly within the finance function.  

Some of the claims have been wildly inaccurate. This is mainly due to confusion among the public and the media regarding what the three areas actually constitute.  

To clarify: 

  • Intelligent automation is merely software following instructions. 
  • Machine learning is based on algorithms that allow computer programs to automatically improve and evolve through experience. 
  • Artificial intelligence is a bit harder to define but, in a nutshell, it is the process of making computers behave in ways that were previously believed to require human intelligence. 

Taken in combination, these elements present opportunities in two key areas: 

  • Process efficiency 
  • Business insights 

Build processes that boost efficiency

If we consider potential efficiencies, the opportunities for gains are high. McKinsey & Company have shown that technology could be used to fully automate 42% of finance activities and mostly automate a further 19%. 

These activities primarily consist of: 

  • Tasks required for standard management reporting 
  • Consolidating and validating budget and forecast inputs 
  • Gathering and cleaning data for analysis 

These steps are merely task automation but it’s clearly an excellent place to start given how great the potential is for freeing up the finance team for other, value-added, activity.  

The approach we suggest taking (a view McKinsey share) is to rethink the people and processes in your team, applying the technology where applicable.  

  • Don’t have your team members engaged in time-intensive activities that aren’t adding immediate value. Apply a technology solution to these necessary tasks in order to focus collective brainpower on the more valuable tasks which would benefit from the hands-on attention of a person rather than a machine. For instance, IBM Planning Analytics on Demand reduces build time by using AI to transform spreadsheets into cubes of information. 
  • Focus on the process first and make the technology work towards it after. The finance team needs to lead the transformation to create a system that will save time and money rather than having an IT project foisted on them. TM1’s ‘black box’ allows finance to build exactly what is required rather than settling for an off-the-shelf solution. 
  • Rather than looking to reduce your costs, aim for increased value. Instead of generating the same output with fewer resources, focus on boosting performance and productivity.  

Achieve greater insight

If automation drives efficiency, AI and machine learning lead the way in delivering greater insight. Combing through data to identify patterns that your finance team don’t have the time – and sometimes awareness – to find, these technologies can be used to reveal new insight and improve decision making within the business. Not only are your finance team able to develop a better understanding of what lies behind the numbers, they’re uncovering the information more efficiently. 

Artificial intelligence is still a long way off replacing the complexity of the human mind. Rather than acting as a substitute for your team, this technology should be used by your team to enhance their ability to make profitable decisions. To use a phrase from IBM’s Ginni Rometty, it should perhaps be known as ‘augmented intelligence’ for what it can deliver to FP&A.  

Specific applications

There is clear business value to be derived from making the most out of the capabilities of AI: 

  • Testing hypotheses. Having the ability to create a model (within sandboxing in Planning Analytics this can be done without impacting on any existing planning) and use AI to project specific patterns forward reveals insights that would be impossible to achieve with less sophisticated technology.  
  • Speeding up decision making. Faster access to more reliable information equips your team to make far quicker decisions. 
  • Triggering data-led actions. AI can alert you, in real time, to unexpected patterns and make recommendations for different outcomes when variables change.   

Get started

The notion of AI, machine learning and automation doesn’t have to be overwhelming. If you take the first steps of improving your processes and increasing your efficiency, you’ll see immediate, tangible gains from making the most out of the technology available.  

Using the Planning Analytics software will enable you to release current constraints on the FP&A brainpower available, creating the capacity to augment the insights that your team can provide. Get in touch today to find out more about the first steps to making this technology really work for you.  

Simon Bradshaw

I have worked in finance and business systems development since 2001 and am an associate member of the Chartered Institute of Management Accountants. In 2016 I became a founding member of Spitfire Analytics, a consultancy specialising in IBM Planning Analytics. We are committed to building long-term relationships across all industries. I focus on my CPD through CIMA and IBM badges, ensuring I am always abreast of best practice and developments within the industry.


Spitfire have a depth of understanding not only in Cognos/TM1 technologies, but also in finance and accounting. It is this combination of expertise and their ability to get to the heart of business problems that has resulted in such confidence in their delivery and capabilities. The insight and value-add they have brought is evident.

- Peter Smith, Head of Solution Delivery, Edrington

Request a demo →

  • This field is for validation purposes and should be left unchanged.