Exploring the Potential of Generative AI in BusinessPublish Date: September 22, 2023
When I engaged a generative AI tool in a direct inquiry about its potential contributions to businesses, the response revealed the fundamental capabilities of this technology; data security, training and knowledge sharing, customer support to quote a few. While this is only a glimpse into what the basic version of the tool can do, it hints at the incredible potential of its advanced capabilities. Intriguing. Isn’t it?
Generative Artificial Intelligence, or “gen AI”, is gaining prominence at a breathtaking pace, and it’s not without reason. The latest annual McKinsey Global Survey on AI paints a vivid picture of the explosion of gen AI tools and their impact on organizations worldwide. Less than a year after their debut, a staggering one-third of the surveyed organizations revealed that they already use gen AI in at least one business function. This is not just confined to tech-savvy employees; it’s become a topic of interest for company leaders, with nearly one-quarter of C-suite executives using gen AI tools for their work.
Furthermore, approximately 40 percent of businesses in the same survey stated that their organizations intend to increase their overall investment in AI, driven by the remarkable advances in gen AI.
Impact Across Industries and Business Processes:
The impact of gen AI is not limited to a particular sector; it can disrupt various industries. Hi-tech companies, unsurprisingly, are at the forefront, with the potential to add value equivalent to up to 9 percent of global industry revenue.
However, it’s not just hi-tech; knowledge-based industries such as banking and pharmaceuticals could see up to 5 percent added value. Even education, a traditionally conservative sector, might experience up to 4 percent impact. This starkly contrasts previous technology waves that primarily affected manufacturing-based industries.
Applying Gen AI:
From marketing and sales to product development and service operations, it’s making its mark across various business functions. It’s optimizing product development cycles, streamlining risk and supply chain management, and enhancing HR functions, among other things.
The most commonly reported uses of generative AI tools
Share of respondents reporting that their organization is regularly using generative Al in given function, %1
Manufacturing: Although manufacturing industries may experience less disruption, generative AI contributes to quality control, predictive maintenance, and process optimization. A recent study by IDC identifies manufacturing (production), product development and design, and sales and supply chain as the key areas where generative AI is expected to have the most significant impact in the next 18 months.
Healthcare and Pharmaceuticals: In the healthcare and pharmaceutical industries, generative AI can transform research and development, patient support, administration, data analytics, and more. In pharmaceuticals, it enables the automation of complex processes prediction of drug candidates and facilitates the design of innovative therapies, leading to breakthroughs in treatment options and better patient outcomes.
Education: It transforms education by creating tailored learning materials, adapting teaching methods, and automating grading, benefiting students and educators alike.
Retail: In the retail sector, gen AI personalizes the shopping experience, optimizes inventory management, and automates routine tasks, enhancing operational efficiency.
Challenges and Future Growth
Organizations need to establish policies governing the usage of gen AI technologies, leaving room for potential misuse. Inaccuracy is a common risk associated with gen AI, with just 32 percent of respondents actively mitigating it, suggests recent industry reports. This is even lower than the percentage of organizations addressing cybersecurity risks. While this may be true, Gen AI is also critical in data breach response. Organizations that extensively use both AI and automation experience a data breach lifecycle that is 108 days shorter compared to those not utilizing these technologies.
As we journey further into the world of gen AI, its influence on business operations and workforce development will be immense, but it is not without its challenges. Ethical considerations, data privacy, and robust regulation must be addressed. Ensuring that AI-generated content aligns with human values is a decisive factor in its adoption.
Global Head of Digital and Infrastructure Services
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