There are three most relevant technology innovations for finance in the next five years, said Gartner recently when releasing its “Hype Cycle for Emerging Technologies in Finance, 2023”.
Given that evolving and future-looking nature of these most relevant technology innovations for finance are included in this Hype Cycle, Gartner recommended that finance leaders need to select technology innovations that align best to their organisational needs.
In addition, organisations also need to develop short- and long-term roadmaps to align finance to developing trends, and allow themselves to evolve gradually, the advisory firm noted. .
“Begin with small steps and lower-risk iterations not only to avoid big mistakes but to give the finance organisation time for such gradual evolution,” advised Mark D. McDonald, senior director, research in the Gartner Finance practice. “Over time, iterative cycles of improvement will cover a broader range of processes and responsibility.”
The three most relevant technology innovations for finance are as follows. According to Gartner, they stand out as being on a path to mainstream adoption within five years and having transformational potential for the finance organisation.
In a departure from the monolithic and inflexible technology applications commonly associated with enterprise technology, composable applications have arisen in response to greater demand for business adaptability in more volatile times.
Composable applications, are modular in nature and are built to support fast, safe, and efficient application changes in the face of frequent disruption and new opportunities. The improved agility of business technology drives resilience and adaptability throughout the business.
Composable applications are built as flexible compositions of well-packaged modules of business application capabilities. The “composers” tend to be a business-IT fusion team while the creators of the modules may be application vendors or central IT software engineering teams.
Decision intelligence (DI) is a practical discipline used to improve decision making by explicitly understanding and engineering how decisions are made, and how outcomes are evaluated, managed and improved via feedback.
The current hype around automated decision making and augmented intelligence, fueled by AI techniques in decision making has revealed the brittleness of legacy business processes in this new environment.
An increasingly complex business environment, with an increasingly uncertain pace of business, and ever more decisions taken by machines have created a sense of unease from the human and also regulatory perspective. There is a need to transparently represent how decisions are being made.
From a pure business perspective, it makes sense to curtail unstructured ad-hoc decisions that are siloed and disjointed, and properly harmonise collective decision outcomes across an entire organisation. Software tools are now emerging that will enable organisations to practically implement DI projects and strategies.
ERP rollouts of the last decades focused on collecting transactional data. Now, finance organisations are burdened by the quantity of information collected and don’t know how to analyse or use it.
A new breed of software vendors is introducing intelligent applications (IAs), which are entering at the Peak of Inflated Expectations. These applications are augmented with AI and connected data, from transaction and external sources, to generate a system that provides contextualised features, experiences, and processes, and can continually learn, improve and adapt.
The promise of such platforms is that finance can spend more time on business support and use limited in-house AI resources to build business-specific AI-driven solutions.