3 ways to elevate your AI marketability

Garreth Hanley:
This is INTHEBLACK, a leadership strategy and business podcast brought to you by CPA Australia.

Hello and welcome to another episode of INTHEBLACK’s Career Hacks.In this series, we'll bring you the latest strategies and tips to supercharge your career.

Today, we are speaking with Stephanie Jonovska FCPA about how technology is automating day-to-day tasks and transforming the finance and accounting profession.

Stephanie is head of finance, operations and transformation at Blue Scope Steel, and she's the chair of CPA Australia's Digital Transformation Centre of Excellence. Stephanie's experienced in how technology can benefit accounting and finance operations.

Welcome to INTHEBLACK, Stephanie.

Stephannie Jonovska:
Thank you, Garreth. Well, I wanted to start by saying what a privilege it is to be a finance professional in the AI generation. And who would have thought that, after more than 30 years' experience, I would still be having fun? But this constant change and learning has been incredible and certainly shaped a career I love. So today I'll share some tips for those at any stage of their career and also digital journey.

Garreth Hanley:
It's great, Steph. It's great to hear you're still enjoying it. I'm wondering, when did you first encounter RPA, or robotic process automation. And for listeners who might not have heard about it, what is RPA?

Stephannie Jonovska:
I first encountered RPM in India around 2017. It was being used by an organisation to automate the accounts payable process, and I was totally blown away by watching this being process invoices on the screen as a digital assistant to humans. It was just amazing. So, what is RPA refers to robotic process automation. It's a software robot that mimics what a person does with their mouse and keyboard. It really excels at high volume, manual, repetitive, very standard processes. It can log into any application. That's right, any application. Upload downloads great data and do calculations. In my view, RPA is really good for removing waste or what we call “wombats” – waste of money, brains and time – and after all, our most important resource is our people's brains and time. If they're doing mind numbing tasks and we are paying for it, it's not acceptable.

We use a framework to ensure we focus on the right use cases, and I'd like to share that framework. It's called ESOAR. The letters stand for something really important, so the E is eliminate – any waste in the process, get rid of it. S is standardise – minimise variations to a process, go vanilla. O is my favourite letter by far, by the way. It's optimise. Optimise means sweating your investment in any system, making sure you push it to its limit. A is automate using typically off-the-shelf products, and R as robotics – do last. And it's really important – you don't want to put a robot on a broken, non-standard wasteful process. You just get a faster, broken, non-standard wasteful process. And in my view, there's a lot. Of value you can get from the E, the S, the O and the A before you get to R.

Garreth Hanley:
So, no WOMBATS and lots of ESOARs, is that right?

Stephannie Jonovska:
That's exactly right. But I think giving those frameworks really helps people come up with the right problems to solve.

Garreth Hanley:
So how is automation changing the role of finance professionals?

Stephannie Jonovska:
Automation is changing the role of finance professionals in three key – and in my view, very exciting – ways. One is creating that capacity again, that removal of the wombats, freeing up our most valuable asset, our brain, to do impactful work, drive improvement projects, innovate with the business, work on your own capability and more time to be that awesome finance business partner that we aspire to. Secondly, it builds our capability. We are learning how to work with machines as our coworkers, and to me that is a very critical skill right now. And lastly, we can upskill, in actually developing these automations, adding to our skills toolkit. A really practical example for us was the tedious task of copying data from one system to another during budget time, which required 10 accountants to spend a day each doing this task. Can you imagine? Copy paste, copy paste, copy, paste, not a very fun task, nor a good use of our brains.

So, a finance person who lives through this and absolutely hated it upskilled in book coding and automated this copy paste, copy paste, using RPA. So, three key things happened. It saved the mind-numbing task of doing this over and over again and over 100 hours was saved, which is now being repurposed. Those 10 finance business partners were exposed to working alongside a bot, demystifying the technology and making it very real. And the finance person was trying to automate the process, and this is actually called a citizen RPA developer, a non-IT person who learned to code. This person subsequently went on to expand their automations and became our digital finance and innovation lead. So, he's got a completely new career path as a result of this.

Garreth Hanley:
You spoke a little bit there about programming. It sounds like moving data might be as enjoyable as moving house. Do you have any other tips for different technologies other than RPA and maybe a little bit of programming that finance professionals should consider learning?

Stephannie Jonovska:
I'll start with a hot tip from me. Learn technologies that will have an impact on your organisation’s problems to solve and will be good skills for you to have for your career. So, the first step is to identify a problem you or your organisation have and learn how to apply technology to solve that problem. You might learn a skill yourself, or work with IT, or with another partner, but really learn. I'm going to give you some practical examples. If you struggle with delivering data and insights to the business, using tools like Power BI, Tableau,data analytics and visualisation tools that can help with data cleaning and combining data from different sources and showcasing that. If you have challenges predicting sales, cash flow, EBIT, potentially machine learning could be useful.

This is a slightly more challenging skill. It relies on data engineering and data science abilities, but for finance people, knowing how to use and explain this is probably more crucial than the actual coding. You're likely to need to work with IT or an external partner. But if you want to match cash collected from customers to invoices or like audit your payments for potential duplicates, which is something we do, then use AI. There's a lot of ready-made solutions you can implement with again help the IT partners. You may not need to create them yourself, but knowing how they work, what issues they address, and importantly interpreting the outcomes are important skills as well. I'm going to give you another practical example that we use in our business.

Our challenge was to merge more than 100 spreadsheets to summarise our finance capability review. So, everyone completed this review. Imagine how difficult that would be to do manual in Excel and then derive insights or implications and then actions of course. One of my team members learnt Python, consolidating the data and then presented it in Power BI. Big impact now guiding our next steps for our capability improvement program. So, this is the first time we've been able to use a data-driven approach to our own capability review at scale. So again, using digital tools to solve a problem, demonstrates the value. Importantly, we've also learned skills, including Python, which can be now used to solve other problems.

Garreth Hanley:
It's really interesting, Steph. It sounds like key in that process is actually identifying the problem before identifying the solution, would you say?

Stephannie Jonovska:
Absolutely. I often go around saying I get about a dozen cold solicitations a week saying do you want to buy this, how about this, how about this. I'm not interested if I've got a problem, I'll work harder to understand that problem and do some what we call digital sensing, which is what's the right tool to solve the problem that we're faced with. Don't just jump at a shiny item and think about your problem to solve, and then find the right solution to solve that problem.

Garreth Hanley:
So, for accountants and people in finance teams out there, it sounds like these technologies are blurring the line a little bit between IT and finance. Does this mean that that our listeners need to go and learn programming?

Stephannie Jonovska:
Absolutely the boundaries between IT and finance are blurring. I think we've still got very distinct roles. For accounts, digital skills are a great asset for your career, a career differentiator. It makes you very attractive to employers, you combine the superpowers of finance and IT you are very marketable in my view. My digital finance and innovation team members who work closely with IT and the business to deliver digital projects, fortunately, or maybe unfortunately depending on how you look at it, often get approached for roles both in and outside the organisation. Proficiency with programming languages such as Python or SQL, RPA, advanced data analytics is where the blurring is occurring.

However, you know I have a slightly different view on these, these are important skills that are also applicable to other functions, so that gives you diverse opportunities. You can use these skills to take your commercial career into sales and to marketing to procurement, into operations. So, I think it gives you a broadening of your career opportunities. Two important things to consider are our role can be to partner with IT so you can work collaboratively with an IT department, if you have one data scientist, other partners to drive business value. I think this can be quite a superpower too, actually.

I have found the ones who excel in this area can communicate in both business and IT terms I call it IT-ish. When I first met our data scientist and started working on machine learning with my team, I didn't understand the language he was speaking. Things like features and drift, but I asked questions and I stayed curious. I value IT expertise, but I also knew we had problems to solve and using great IT skills combined with our business skills is a great combination to solve business problems. So, think about that partnering with IT. In terms of the question about do we need to program. I think continuous learning for accountants is absolutely critical, for Australia, we expect to have a digital workforce gap of 370,000 by 2026 according to predictions.

Garreth Hanley:
A lot of people.

Stephannie Jonovska:
That's a lot. Yeah. So, in my view, we all need to be digital workers. As accountants, we need to keep learning constantly in small, manageable chunks. Everyone's cognitively overloaded now. But making sure we can apply it in practice, now me personally, I read a lot INTHEBLACK articles, digital articles from CPA Australia. I've done digital micro credentials and some online courses through platforms like LinkedIn. I recently finished data governance for everyone course it was so useful I could use it in my next meeting and use it to explain why data governance matters. That sounds like the most boring topic ever, but good data governance leads to good, trusted data and we can extract value for that. So I am using some IT language a bit, but I'm also adding a business perspective. Which I think is really important for us as accounting professionals.

Garreth Hanley:
Have you found that accountants oftentimes have a more solid base to work into this area than they realise. That maybe they understand business processes, they understand how to run a spreadsheet which includes some programming, and they also understand the importance of good data.

Stephannie Jonovska:
Absolutely, they are primed for roles that straddle into the digital area and often undersell themselves, as you said, great respect for data, know how to wrangle data, you know, across the business problems to be solved as well. And I think this is where we can really embrace that superpower of joining our finance and accounting skills with digital to giving in better results for our people. And again to give us all great careers as well that are very relevant and marketable in this AI generation.

Garreth Hanley:
Are you seeing new types of finance roles or is it more a case that people are adding these skills to their current roles and doing more?

Stephannie Jonovska:
It’s a bit of both, I am seeing new roles, and I feel obliged as a finance leader to almost create these roles before we even know we need them. A year and a half ago, we didn't have a digital financing innovation team. Now we have three key people – a manager, analyst and specialist. They have several focu ses, you know, develop framework and ways of working, which includes something called our ideas hub. It's a digital system to capture, prioritise and monitor projects and delivery. They implement projects with the business and IT, that's all about value delivery.

We talked about capacity creation, but also improved employee experience. And the third area is upskilling, they do some blended learning on the job training, mentoring, tech teachers. In our team goals, they also have an ambition to accelerate experimentation and implementation of new ways of working. So that means they themselves have a high learning focus – large language models, Python, AI use cases, there's about 15 things they use. But this is really powerful because they do that work of digital sensing. What tool will solve the problem that the business is facing? And another thing I wanted to add, Garreth – this is never ending, my views on this – learning to work with AI and tech and your coworkers. It's a different mindset.

It's also really critical, but as finance professionals, we must still understand and own our numbers. I n my organisation we now have in-business finance partners, our credit team and my team, working with machine learning models. Beautiful news for forecasting. It's a good example of human plus machine equals better – better results. And that is one of the most critical upskilling aspects. That mindset. It's human plus machine, not human versus machine. And again, I'm going to stress it. As finance professionals, we own the numbers regardless of whether it's a human only or a human plus machine. And in my view, we have failed if we can't explain the numbers and say, “Oh the machine told me that”, unacceptable. We have the brains that we need to use in this space, “the model in this example won't necessarily know if there's a weather event that's going to impact delivering invoicing”.

You need to overlay your knowledge to machine outcomes. We need to broadly understand how the models work and make sure the model is explainable. And that would definitely mean upskilling. No matter how these numbers are produced, we own the numbers, and that is our role. That is really our ticket to the table really, that's where you add your value, you understand the numbers you explain the numbers. You use the numbers to make decisions and help the business navigate through strategic challenges, no doubt.

Garreth Hanley:
So, you can't just have a black box and expect the black box to give you the right answer?

Stephannie Jonovska:
No, you can't have a black box. I like the glass box and starting to make it much more transparent and things like explainable AI and other things can help in that area. But importantly it's that mindset, human plus machine equals better, and I own my numbers and must be able to confidently speak about it.

Garreth Hanley:
From what you've just said, I have a feeling I know the answer to this next question, but how important is it to have a technology experience as a CFO?

Stephannie Jonovska:
You already said it, it's not just an asset for CFOs, it's an absolute necessity. If you look at what CFOs have on their plate right now – inflationary pressures, talent competition shifts in what the customer wants, technology transformation, cyber security concerns, ESG investment and everyone wants you to be a trusted business partner. Technology can help address many of these challenges, so if you take a strategic lens in terms of driving digital transformation, a CFO with tech experience, can lead these initiatives.

They can identify opportunities for tech to streamline operations, enhance finance reporting, improve decision making processes, and what I'm seeing more and more of is CFOs driving enterprise-wide transformation like ERP or enterprise resource planning replacements and upgrades. So, I think that's a really good role for the CFO to play. Another strategic element, better finance business partnering. We're all talking about it; we all want to do it. CFOs with good tech experience go hard at data, provide more informed and really strategic decisions, good business cases, driving innovation, better business results.

It means you've got to be super familiar with data analytics tools and the techniques that uncover trends, risks, opportunities, all that strategic planning comes with that good stuff, and it leads to innovation. CFOs that understand tech are more likely to lead initiatives that use emerging tech to create new business models, enhance the customer experience and also generate new revenue streams. That is where knowing tech can really help you. If I take an operational lens, all the things we talked about that automation and process improvement, you can help create capacity and work on that more value-add, increase the employee experience.

It's super important in that war for talent, people want to do valuable work and not linking spreadsheets all day. And the last operational lens I'll talk about is the cybersecurity awareness. A really tech savvy CFO will implement really robust measures ensuring that our very sensitive financial data is protected from breaches and fraud. So, in my view, I think it's clear it's mandatory versus nice to know, now.

Garreth Hanley:
And going back to what you started with at the beginning, it keeps things interesting.

Stephannie Jonovska:
Oh, absolutely. The roles are evolving continuously. I think this is a really exciting time to be in finance and accounting, and the more you embrace this technology and digital, it's a career differentiator in my view.

Garreth Hanley:
So, Steph, what advice do you have for people who are wanting to build technology skills?

Stephannie Jonovska:
I would start with identifying your goals. What's your career objectives and goals? So, take a little bit of time to do that. I know it might sound like I should just jump in and get something going. Yes, you can, but make sure it's purposeful, right? And then start with the basics in my view. Build some foundational skills, understanding the basic principles of data governance, data analytics and management, some basic coding is probably the way to go. And the reason I say data is that good data is the foundation for more almost all automation and AI initiatives.

The second thing I would do is build that practical capability, put what you learn into practice straight away through a project and practical exercises. You may need to put your hand up for a particular project or solve a particular business problem but put it into practice. There's nothing worse than doing a course or upskilling and then have nothing to implement it on. And the other areas to stay current, this is moving super-fast. This is moving so fast, perhaps subscribing to some tech blogs, listening to some podcasts reading some newsletters, workshops, webinars, networking with others.

I think there's a lot of power in social learning, so community and mentorship, and in my organisation I'm really proud that some of our finance people are being mentored by our digital finance and innovation team. Because it's that on-the-job social learning that's having a really good impact, because it's support as you go when you need it most. So again, if I haven't made clear, Garreth, if you want to stay relevant and marketable in the AI generation, staying curious and being a lifelong learner is really important. So hopefully there's some practical tips there around how to make this real.

Garreth Hanley:
Thanks, Steph. There's some really good tips there, so I guess the last question I have and it might be the question of the epoch actually is what are your thoughts about the fears that AI is going to replace accountants?

Stephannie Jonovska:
Really critical question. What are our people being constantly told by the media? AI and automation is going to take your job! There's so much fear out there, I like to flip it, AI doesn't replace people, people who use AI replace people who don't. So again, I'm going to reiterate, if you want to be relevant and markable, then you definitely need to understand, use and benefit from AI. Always reinforce seeing that human plus machine is better than either alone, and taking our people on that journey is really, really important to implementation success. Now in my organisation, not one person has been replaced by AI or ML. Has their role changed from data wrangling and crunching and trying to understand very aggregate numbers to being able to add their human knowledge and explain the results supported by great data? Absolutely. It adds so much to a positive employee experience.

And I'd like to go back to history on this one a little bit too. Excel removed 400,000 jobs and then 600,000 new jobs were created 50 years ago. And I truly believe new and different roles will be created. I went on Seek before this podcast, online job search engine. Any of them you can go on any of them and I just typed in AI, 827 jobs were returned. I typed AI in finance, 187 roles AI and accountant, 102 roles. I saw CFO roles, senior financial accountant, business systems analyst. So, there are firms and roles that use AI right now. And in my view, you need to be acting now so that you are marketable and relevant. I might finish off, I think by saying, Garreth, I think it's a really exciting time to be an accountant if you embrace AI and automation. Keep investing in your skills, focusing on areas that require human judgement. You can both thrive and drive innovation for your organisation, and also have a great career in the AI generation.

Garreth Hanley:
Thank you so much for sharing your story and insights with us today. Stephannie, it sounds like the future is bright.

Stephannie Jonovska:
This is one of the most exciting times to be an accountant. I think again, it's a real privilege to be in this profession during the AI generation. So again, a call out to embrace it, keep going hard at the human skills and remember the human plus machine can equal better, but you must understand and own your numbers.

Garreth Hanley:
Thank you for listening to INTHEBLACK career hacks. If you're looking for more career resources from CPA Australia, you'll find links in the show notes for this episode. And until next time, thanks for listening. If you've enjoyed this episode, help others discovering the black by leaving us a review and sharing this episode with colleagues, clients, or anyone else interested in leadership, strategy and business. To find out more about our other podcasts, check out the show notes for this. Episode. And we hope you can join us again next time for another episode of INTHEBLACK.