Currently artificial intelligence (AI) and machine learning (ML) is havi. In terms of accounting and finance, is AI & ML a gift or curse for us? The answer largely depends on two key variables.
In the first FP&A Board Connect, Takeshi Murakami, Business Manager to CEO/President at Microsoft Japan, a speaker of the second Tokyo FP&A Board, explains how Microsoft achieved remarkable results by using predictive analytics and machine learning in FP&A.
“Go to the cloud” has been a key building block in every global CIO’s digital strategy. However, as the CFO, do you find yourself getting into frequent arguments with them over the savings promised at the time of embarking on this journey?
The explosion in computing and data processing power has led to an exponential increase in data available to the business. Paradoxically, this has led to business leaders becoming more uncertain about what to do with this data. Hence, business is scrambling to put the appropriate “analytics” capability in place. This generates a lot of friction and tension because business leaders and managers, who have been brought up in a very different world, have to scramble to learn new languages and redress their relationship with data.
This article will focus on is the modeling of a company as a whole, its consolidated future financial positions, incomes, growth and risks, as opposed to the detailed budgeting of one specific aspect of a company’s business, such as how to increase contract to sales conversion rate.
As I walk around various offices or even in social gatherings, I find many conversations about artificial intelligence (AI), robotic process automation (RPA), and big data. And logically, then, the discussion quite often rolls into how our life will change due to the availability of data, how each of our actions is turning into data, how future consumer behaviour thus can be predicted etc. Thus people quite often discuss predictive analysis (PA), and we hear stories about its use in elections to predict voters' behaviour, customer behaviour, payment risks, etc.