000			01745nam a22001697a 4500
005			20250226120048.0
008			250226b ph ||||| |||| 00| 0 eng d
022			_a0021-8448
040			_cOCT
100			_aAxson, David
240			_aJournal of Accountancy / _hOctober 2024
245			_a5 steps for finance to guide AI investment / _cDAvid Axson
300			_aVol 238 (4) pages41-44 : _billustrations ; _c27 cm
500			_aSince the launch of ChatGPT in November 2022, artificial intelligence (AI) has gone from a niche technology to a purported agent of transformational change in everything from disease diagnosis health care to fraud detection. Goldman Sachs estimates that global investment in AI could reach $200 billion by 2025. As finance professionals, we have been here before. Each new technology - such as ERP systems, data warehouses, e-commerce, and data analytics - is touted as the solution to myriad problems and the creator of new opportunities. Reality has been a little different. Each of these technologies has changed finance in its own way, but none has been the panacea that was originally promised. The reality is that no single technology is the answer. Al may be an-other, potentially powerful, addition to the business toolbox, but there is no such thing as a stand-alone AI business case. There are only business cases that holistically evaluate the technology and human elements that must work together to deliver value. As finance professionals field an increasing number of business cases relating to Al applications, here are five steps they can take to become effective partners in assessing and adopting Al across the enterprise.
653			_aAccounting & reporting / technology
942			_2ddc _cCR _n0
999			_c10269 _d10269