Organizations are currently in the process of implementing generative AI tools on a wide scale. This trend involves the integration of advanced artificial intelligence technologies into various company workflows and systems to enhance productivity and efficiency.
For instance, PwC US is launching ChatPwC, an internal AI tool powered by OpenAI and hosted on Microsoft Azure, to all 75,000 employees by year-end. PwC's Chief Products & Technology Officer, Joe Atkinson, who has three decades of experience, remarked that the exaggerated excitement about AI surpasses anything he has witnessed. AI can potentially transform every aspect of our lives, which he shared during an AI strategy session for chief financial officers at the CNBC CFO Council Summit in Washington, D.C.
What Will It Cost?
Chief financial officers and other C-suite are actively discussing whether to deploy AI as it becomes increasingly essential across various sectors. Prominent business leaders express the view that it's not a matter of whether AI will be implemented but rather when it will be integrated into their operations.
A recent survey of CFOs at the CFO Summit revealed that 44% anticipate implementing tech tools like ChatGPT will result in a net cost over the next 12 months. In contrast, the remaining 56% believe that AI will lead to cost savings in the short term, even if the potential productivity gains from artificial intelligence are apparent.
Extended AI Integration ROI
Eric Kutcher, a senior partner and CFO at McKinsey & Co., aligns with the group that expects the return on investment to take longer than a year. He mentioned running experiments, acknowledging that some might fail at the CFO Summit. While expecting cost savings over a few years, he admitted that in the next 12 months, spending on evolving large language models may exceed returns, and he anticipates encountering some setbacks along the way.
After their first female partner, McKinsey developed an AI platform named Lilli to help consultants accomplish tasks in minutes that would have taken weeks. Forty-five thousand employees now use Lilli, and it has significantly increased productivity. Consultants are using it for various purposes, including efficiently creating client presentations.
How AI Impacts Productivity And Efficiency on Companies
Growing the U.S. economy, even as workforce participation levels drop, will mean that employee productivity has to increase, and finance chiefs view AI as a prime tool for making that happen.
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PwC U.S.
Atkinson explains that the tool can manage various daily administrative tasks for employees, which frees up their time for more strategic projects, maximizing productivity and delivering excellent value to clients. PwC established its internal "AI factory" a year ago, generating over 3,000 potential applications within six weeks. Atkinson notes that most of these ideas have originated from individual contributors rather than leaders.
Atkinson advises organizations to monitor licensing and deployment costs as major tech providers invest heavily in AI tools and upgrades to existing products, including core productivity suites, finance applications, CRM tools, and Human Capital applications. While large language models will eventually become standard, the real value lies in customization at the firm level. However, this cost reduction may take a year or more to materialize. The primary challenge is not the business case versus the price but preparing the workforce for widespread AI usage.
Doximity
Anna Bryson, CFO at healthcare tech firm Doximity, highlighted AI as a powerful tool for enhancing the productivity and efficiency of physicians. She emphasized doctors' challenges in managing a constant influx of new information. She explained that the company leverages AI and machine learning to simplify this process.
Simultaneously, Doximity is using AI to reduce doctors' administrative workloads. Anna Bryson pointed out that for every hour physicians spend with patients, two hours are devoted to administrative tasks such as insurance claims and chart maintenance. AI is helping to decrease the time doctors spend on these non-patient-related tasks.
Palantir Technologies
Likewise, according to CFO Dave Glazer, the main objective of data analytics company Palantir Technologies is to enhance efficiencies and provide insights to clients through AI. He mentioned that the company has been utilizing machine learning for an extended period and is implementing AI in enterprise data to improve operational decision-making.
He recognizes the ongoing AI "hype cycle" as a sign that this technology is enduring. Consequently, Palantir has adjusted its market approach by providing one- to five-day AI "boot camps" to current and potential customers. The company encourages participants to bring their data to the boot camp, allowing them to develop use cases on Palantir's platform quickly.
AI Adoption
Regarding the initiation of AI adoption for CFOs, Bryson from Doximity suggests a gradual approach. The company has already invested in AI for sales forecasting. Even if they find the software less helpful in the future, Bryson believes it's worthwhile. The tool not only assesses pipeline health but also aids in understanding market trends by account and industry, making it valuable for experimentation.
McKinsey's Kutcher expects AI costs to decrease over time but sees it as a multi-year process, not something happening in the next six months. He emphasizes that the focus should not solely be on the immediate cost efficiency of the technology but rather on how to utilize it for productivity or revenue recognition.
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