Digital fluency vs digital literacy: Why the difference matters

When Simon Lesch, APAC AI and transformation lead at Archetype, speaks with finance teams about how they use digital tools, he hears a familiar story: organisations are not short on technology, they are just trying to determine which tools add value and how they should work together.

The issue often is not access, it is more about capability and understanding what is possible, he says. “There is no shortage of options, and each promises to solve everything. But if people are not trained to use the full capabilities of a platform, or key features are not enabled, they quickly become overwhelmed and organisations fail to realise the full value of their investment.”

While most professionals are digitally literate, true digital fluency comes from understanding how systems connect and using that insight to build smarter, more efficient workflows. In many organisations, the technology stack is doing its job, but the gap lies in integration, where manual processes continue to bridge systems that do not naturally align.

Tyler Wise FCPA, partner at Findex and a member of CPA Australia’s Digital Transformation Centre of Excellence, sees the same pattern.

“The tools are already there: spreadsheets, dashboards and reporting platforms. Yet in many organisations, they are used in isolation and are patched together by manual steps, workarounds and duplicated effort,” he says.

The issue, Wise argues, is not basic capability, but the gap between knowing how to use tools and using them well together. It is the difference between being digitally literate and fluent, he adds.

“Digital fluency is about understanding how systems fit together and using that to design workflows that are connected, automated and scalable,” he says. “More broadly, it is the ability to lead how technology is applied and to embed that thinking across an organisation.”

AI in enterprise environments

Fluency also shows up in how embedded tools are used. Rather than relying on external systems and manual transfers, there is a shift toward artificial intelligence (AI) built directly into the platforms people already work in, says Lesch.

“For many years, AI sat outside core workflows. It was treated as an external tool and you would step out of your primary system, generate outputs and then manually bring those insights back into your day-to-day platforms,” he says.

That separation created obvious inefficiencies, he adds, and only recently have major providers begun to close the gap. Tools such as Microsoft Copilot and Google Gemini are increasingly being integrated directly into enterprise environments.

“Instead of switching between systems, users can now access AI directly inside the applications they already work in by opening a side panel, querying data and generating outputs without leaving the platform,” Lesch says. “It is a shift that fundamentally reduces friction and brings AI closer to where the work actually happens.”

Review workflow structures

Wise points to a common accounting workflow as an example of where many organisations still fall short.

“In many cases, you will see someone using Excel for PivotTables and data manipulation, and then move that output into Power BI, largely for presentation,” he says. “It works, but it is still a fairly linear, manual process.”

A more fluent approach starts by questioning the structure of that workflow itself.

“This is where you start asking different questions: what can be automated, how those tools can be better integrated and whether you are really pushing the existing platforms to their limits,” Wise says. “In some cases, particularly where there is valuable proprietary data, that might even mean moving beyond off-the-shelf tools and building something more tailored to own and automate the workflow.”

A return of time

One of the most immediate benefits of digital fluency is time. When repetitive reporting and administrative tasks are automated, a meaningful portion of the working week is freed up for higher-value work.

“A large proportion of white-collar work, particularly in accounting, still involves repetitive reporting, data preparation and manual data transfer,” Lesch says.

The opportunity is not just efficiency for its own sake, but what that time enables instead: more analysis, stronger insight and better decision-making. The shift is from doing the work faster to doing different work altogether.

“We are now at a point where technology can, in some cases, return anywhere between 5 per cent and 40 per cent of a professional’s time,” he says.

Review and revise

The pace of change in technology can feel relentless. New tools, features and platforms emerge constantly and make it difficult to know where to focus. But fluency, Wise argues, is not about keeping up with everything. It is about being deliberate and regularly reviewing the tech stack to make sure it is still fit for purpose.

“My mantra is ‘catch up, do not keep up’,” he says. “At a certain point, you need to step back and review your tech stack. Ask: what is the best option available right now and is it worth pausing current workflows to consider a tool upgrade or change in approach?

“Ultimately, technology is becoming more accessible and democratised,” Wise continues. “The barriers to digital fluency are less about technical expertise and more about mindset, and having a willingness to experiment, test and refine tools within your own workflows.”