With global volatility and inflation impacting organizations across all industries, business agility has never been more important. Leaders turn to finance teams to get real-time insight into business performance and recommendations on future initiatives that will help them thrive amid disruption. But finance teams are overwhelmed with manual tasks, cobbling together data, and disconnected teams. Achieving game-changing business agility begins with augmenting the human ingenuity of your people with intelligent process automation. When it comes to reimagining processes with AI, automation, and analytics, many finance leaders don't know where to start.

Datarails, the FP&A platform for Excel users, has launched FP&A Genius, "the ChatGPT" for the CFO's Office giving companies unprecedented instant insights about budgets, forecasts, variance, and spend. FP&A Genius provides generative AI answers based on complete and consolidated finance data from across a company. The chat function allows executives to quickly answer questions such as'How did revenue compare 2022 vs 2021?', 'What will happen to the bottom line if inflation is 2x the rate today?' and'How will results be impacted if revenue grows by 10% next year?' Recommended AI: The Future of AI Is Here. Now Let's Make It Ethical The AI feature benefits from the release of FinanceOS also released by Datarails today.

Digital technologies are transforming every aspect of our professional and personal lives. While certainly disruptive, and often the brunt of doomsday futurists, innovations like artificial intelligence (AI) present enormous possibilities to make things work better. They also add some exciting sparkle to traditionally dour (but very important) professions such as financial management. Shiny new image aside, AI is set to transform the financial management sector into a body of strategic, informed, and responsive consultants. There is no doubt that the COVID-19 pandemic has accelerated digital transformation, encouraging many finance professionals to harness the benefits of AI to meet their clients' changing expectations. The well-timed Sage CFO 3.0 research surveyed South African CFOs and other senior financial decision-makers for their views on the role of digital technologies, such as AI, in navigating uncertainty and preparing for the new working world.

It's no secret that agile companies, those that can quickly respond and pivot when necessary, fare better than those that falter when faced with uncertainty or change. A recent IDC global report shows that agile companies experience higher profits, revenue growth and impressive market share gains. They also have stronger employee retention rates, faster time to market and better customer experiences. Yet, being able to adapt to change and successfully deal with the unexpected requires a steadfast focus on the future, and many organizations today are too bogged down with the here-and-now to focus on what lies ahead. As company leaders increasingly search for ways to achieve agility and future-proof their businesses, automation technology is becoming a key initiative.

Our work will be implemented at Rossmann Pharmaceuticals as a Machine Learning Engineer. The finance team wants to forecast sales in all their stores across several cities six weeks ahead of time. Managers in individual stores rely on their years of experience as well as their personal judgment to forecast sales. The data team identified factors such as promotions, competition, school and state holidays, seasonality, and locality as necessary for predicting the sales across the various stores.

Data scientists must handle many aspects of the business, they need to have good technical (coding, Data architecture, and structure) and good statistical skills, but also have a good understanding of the business. Data science can be applied in multiple aspects of the business to solve problems such as optimizing efficiency or automizing the process. Often added to a different department (law, marketing, finance, merchandising, etc.) to support the teams and help them to better performance, especially in Finance. Data Science has become an essential asset to support and ease the analysis in a short period with low human intervention. Finance has always been about data, financial institutions have been the first ones to adopt data analysis, and now it is starting to leverage machine learning and artificial intelligence.

T-Hub, which leads India's innovation ecosystem, announced that it has co-invested in Bluecopa through T-Fund along with Blume Ventures and other notable investors like Titan Capital, Speciale Invest, Bharat Founders Fund, T2D3, Amplify, and Force Ventures. Finance operations automation platform, Bluecopa raised USD 2.3 million in this seed funding round. Also joining the funding round are seasoned entrepreneurs Krish Subramanian, Rajaraman Santhanam, Founders of Chargebee, Rohit Chennamaneni, Founder of Darwinbox, Asad Khan, and Jay Singh, Founders of LambdaTest. T-Fund is primarily a Co-Investment Fund, which invests alongside established Angels, Angel Networks, and venture capitalists. T-Hub is the Investment Manager and will formulate investment and business development strategies for this fund. It will source startups from various sectors, including but not restricted to Information Technology, Cleantech, Agritech, Fintech, Healthtech, Logistics, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things, Augmented Reality (AR), Virtual Reality (VR), Hardware, Blockchain, and Consumer tech.

In development for more than a year, Auto-Itemization from TripActions Liquid is a solution that automatically splits transactions and attributes each line item to specific expense policies. The technology allows a user to upload a receipt for automatic itemisation; using AI, foreign language translation and fuzzy matching, each line item is categorised and assigned to a specific policy with 90 per cent accuracy. The use of machine learning also ensures that accuracy will increase over time. Single transactions often consist of multiple parts or line items -- like variable daily service charges for a hotel stay -- that need to be reported independently for accounting and tax purposes. The cost of the room needs to align with a company's hotel policy, while the room service that employee orders can align to a per diem for meal costs.

Implementing AI across an organization requires a clear strategy, organizational flexibility, a data-driven environment and new forms of collaboration with cross-functional teams.

Artificial intelligence and machine learning (AI/ML) have already transformed industries and changed the way work gets done across the enterprise. While finance has traditionally lagged behind other departments in the AI adoption curve, that's starting to change. Adoption of AI in finance is being spurred by digital natives (professionals who grew up in a connected world), with tech solutions finally delivering on the promise of AI/ML. Finance professionals accustomed to modern technology experiences in other areas of their lives are no longer willing to endure painstaking manual reviews and the threat of inaccurate data in their forecasts and plans. Outside of finance, many other areas of the businesses are far beyond cutting their teeth when it comes to using AI to improve forecasting and drive decision-making.