Generative AI’s Economic Potential: Unveiling the Productivity Frontier
Generative AI (GenAI), with its unprecedented potential to create novel content, is rapidly transforming our world of work and commerce.
By leveraging machine learning algorithms, GenAI can design virtual models, produce new music, generate written content, and predict future scenarios. As a recent McKinsey’s article suggests, this AI-powered technology is not only pushing the boundaries of creative expression but also becoming a powerful tool for a variety of industries, including retail, banking, and pharmaceuticals.
McKinsey’s research concludes that between $2.6 trillion to $4.4 trillion of revenue could be generated annually across the 63 use cases they examined. That said, around 75% of GenAI use cases so far fall within marketing and sales, customer service, research and development and software engineering. Other departments are slower to buy into the AI revolution.
We are probably in an early exploratory phase of discovering what GenAI can do, and how it can partner with human imagination to create genuinely unique products, services, and content.
Yet, already, AI’s impact has exceeded all expectations. Let’s look at just some of the industries that GenAI is already revolutionizing.
Retail and Consumer Packaged Goods
Generative AI is making waves in the retail and consumer packaged goods industry by enhancing product design, improving supply chain management, and personalizing customer interactions.
AI algorithms can generate thousands of design variations in a fraction of the time of traditional methods, enabling companies to rapidly prototype and fine-tune their product offerings.
This is a perfect illustration of the partnership approach. Designers prompt AI to create a panoply of suggestions, then choose between them and use their own finessing skills to produce a finished product. In this collaboration, designers aren’t replaced by GenAI in the same way that modern cameras haven’t replaced photographers. The technology simply provides better creative tools.
As Rob Girling writes in the Artefact Group’s design blog, “until AI is capable of surprising us with completely novel ideas, superstar designers and companies that invest in them will continue to dominate, increasing the value of design brands.”
Currently, there are ethical dilemmas regarding copyright protection and creative ownership, but these issues will no doubt be resolved in time, probably with insights gleaned from current legal test cases.
Fortunately, in other parts of the product supply chain AI’s use is less controversial.
For instance, in supply chain management, generative AI can identify patterns and predict future demands with high accuracy, thereby streamlining logistics and reducing wastage. Pointless errors are avoided, and AI won’t forget a task or assign the wrong priority level to a piece of work.
In entertainment, AI can personalize marketing strategies by analyzing individual customer data and delivering targeted content. Netflix are already using this function with impressive results, as well as employing AI to optimize streaming bandwidth during busy periods.
Banking and Fintech
In the banking and fintech industries, AI is being used to combat fraud, enhance customer service, and improve risk management and due diligence. It can simulate fraudulent activities to help banks enhance their security protocols, and spot patterns that indicate the possible presence of fraud, so that human investigators can optimize their time.
Additionally, GenAI can predict customer needs, providing more personalized service and advice. It can be used to accurately target marketing at customers who are likely to be approved for loans or overdrafts, and achieve higher conversion rates.
In risk management, generative AI can assess various risk scenarios and provide predictive insights, improving decision-making processes. Furthermore, it can handle millions of data points in minutes, or even seconds, resulting in quick yet well-evidenced and thorough assessments.
Machine Learning models can also be fine-tuned for specific client use cases, as Evalueserve has done for several financial clients. This effectively hands companies bespoke solutions their rivals don’t possess, conveying competitive advantage.
Pharma and Medical Products
The pharmaceutical and medical industry is harnessing the power of generative AI in drug discovery, patient care, and medical research. AI can generate molecular structures for potential new drugs or compounds, significantly reducing the time and cost of drug discovery.
This isn’t entirely new. As an article in Forbes points, out, the pharmaceutical industry was one of the early adopters of computer-assisted research, dating back to the 1960s.
As Forbes writes, “the interaction of a drug molecule with a biological system has required the pharmaceutical industry to develop sophisticated workflows where many human experts make pivotal decisions based on expensive experimental data. Once AI proves its ability to solve those complex problems, the whole industry can be transformed into a totally different business.”
For some, that’s a frightening prospect, while others are excited about the pairing of human imagination and expertise with GenAI accuracy, speed, and processing power. Currently, AI is more than demonstrating its mettle in the realms of blue-sky biotechnology.
For instance, Google’s Deepmind AI is helping unlock the secrets of the proteins that power our cells, creating new frontiers for gene therapy. In time, AI may even solve one the biggest philosophical questions of our age, by finding a self-replicating molecule that could be the missing link between organic chemistry and the initial spark of life itself.
More mundanely but nonetheless importantly, AI can analyze patient data to generate personalized treatment plans and even personalized drugs. And in medical research, AI can simulate various medical scenarios and predict outcomes, enabling researchers to devise better strategies and treatments.
Although there’s certainly work to do in reassuring patients that they remain in safe hands, healthcare and medical research are already heavily invested in GenAI and its transformative potential.
The Generative AI future of work: Impacts on work activities, economic growth, and productivity
As the McKinsey article rightly points out, the GenAI-enhanced future of work has profound implications for human activity, economic growth, and productivity. With its ability to automate complex tasks, AI can augment human capabilities and increase productivity.
It can also generate much uncertainty and anxiety. The AI revolution requires a complete overhaul of what work we consider vital for humans to perform, and what can safely be farmed out to GenAI.
One of the less anticipated outcomes of progress so far is the replacement of much of the diagnostic and interpretive work of “white collar” professionals, leaving caring roles largely untouched. In other words, physicians’ roles may be radically reinvented, while nursing is less affected.
If such fears can be quelled, the opportunities are limitless. By taking over routine and mundane tasks, AI allows workers to focus on creative and high-level cognitive tasks. This shift not only boosts individual productivity but also fuels economic growth.
The current consensus seems to be that AI adoption won’t lead to significant job losses, but rather a redefinition of roles, and a change in the priorities that employers hold when recruiting. As Ivana Bartoletti writes in the Guardian, “…AI and automation are most useful in conjunction with human roles – where people can offer the complex decision-making skills or human touch that the machines lack.”
As generative AI continues to evolve, the demand for skills related to AI and data analytics is expected to rise too. Organizations need to invest in reskilling and upskilling their workforce to tap into the potential of this transformative technology.
Predictions for AI-Empowered Growth
Assuming AI and humans can work effectively together to reach ever more dizzying heights, what is the likely economic impact looking forward?
In May 2023, the CfM-CEPR (Center for Macroeconomics / Center for Economic Policy Research) surveyed its members about the expected economic impact of AI on employment and growth.
The results were encouraging. On average, their economists predicted a boost in growth of between 4-6% annually. In addition, the panel members believed AI would not create significant unemployment in developed nations.
Given that McKinsey predicted that, by 2030, 70% of companies will adopt some form of AI, this is good news (although there’s always uncertainty in such predictions). Indeed, Price Waterhouse Coopers were even more bullish, predicting a global GDP increase of 14% by 2030.
Some believe McKinsey may have been overly cautious with their 2018 discussion paper. Statista currently predicts AI will demonstrate a CAGR from 2023-2030 of 17.3%, creating a total market volume of $738 billion by the end of the decade.
However cautiously or optimistically you make such predictions, it’s undeniable that GenAI will have a significant economic impact and that we’re still on the shallow end of the adoption curve.
Evalueserve's role in the generative AI revolution
Evalueserve, the leading global professional services provider, offers AI-powered solutions to help businesses unlock the potential of GenAI.
Our analytics and data solutions, such as Insightsfirst, harness the power of AI to deliver actionable insights and predictive analytics, enabling businesses to make informed decisions.
Whether it’s optimizing supply chains in retail, improving risk management in banking, or accelerating drug discovery in pharmaceuticals, Evalueserve’s robust AI solutions are pivotal in driving industry transformations.
Don’t be left behind in the generative AI revolution. Explore the spectrum of Evalueserve’s solutions here and pave your way to an AI-empowered future.
