The Generative AI Potential: CXO Perspective
A recent global survey done by Freshworks has highlighted that 9 out of 10 (91%) employees are frustrated with their workplace technology. This is despite the pandemic-driven tech spend surge that the world witnessed. According to KPMG, businesses spent approximately $15 billion extra per week on technology to enable remote working during the pandemic. But there still remains a huge gap between employee expectations and employee experience. Globally, the top complaints were slow speeds (51%), slow response from IT teams (34%), lack of collaboration between teams (30%), missing features/capabilities (28%), and lack of automation (25%).
While a fierce war to hire and retain talent is raging globally, CXOs are looking to tap the potential of Generative AI to combat some of the top complaints from their employees. In this blog, we take a look at the potential & impact of Generative AI from the CXO perspective, and the role that it can play in improving business performance as well as employee and customer experience.
Economic Potential of Generative AI
Various sectors are incorporating generative AI solutions into their operational workflows. According to an IBM survey, 35% of participants recognized generative AI as a leading emerging technology expected to significantly influence their businesses in the next three to five years.
The economic impact of Generative AI is substantial, as it has the potential to boost productivity, lower expenses, and introduce fresh value propositions. AI functioning as a ‘prediction technology,’ lowers the expense associated with predictions, thereby reshaping business strategies and potentially resulting in the emergence of new avenues for wealth creation. A LTIMindtree report discloses that 75% of businesses in the United States have experienced a minimum of 5% cost reduction through the adoption of Generative AI.
Organizational Impacts of Generative AI
Generative AI is already being integrated into many common workplace tools such as email, word processing applications, and meeting software, indicating that this technology is poised to fundamentally revolutionize the way people conduct their work. Here are a few ways that we note Generative AI will impact automation in an organization:
- Natural language will emerge as a new automation language
- More internal processes will be automated and handled by Virtual assistants using generative AI like scheduling meetings and answering common employee queries.
- Generative models will be employed to analyse large datasets and identify patterns or trends in data, providing valuable insights for decision-making.
Applications of Generative AI
While the applications and possibilities of Generative AI in the workplace are immense, we are still at the nascent stages of Generative AI and the impact of and predictions for automation with generative AI are yet to be seen.
Here are examples from a handful of specific industry sectors to show the potential use cases for Generative AI:
- Design social media marketing campaigns.
- Create detailed product descriptions.
- Create high-quality videos to demo a product.
- Analyze customer sentiments for hyper-personalized products.
Banking and Financial Services
- Help financial institutions make informed decisions on investment strategy.
- Extract information from reports to summarize insights on financial records, customer feedback, account statements, etc.
- Monitor constantly changing compliance regulations and draft compliance statements with supporting evidence.
Medical and Pharmaceuticals
- Identify test patient populations, simulate trial outcomes, and optimize clinical trials to accelerate drug development.
- Analyse health records to identify patterns indicative of disease states to support faster, more accurate diagnoses and treatments.
- Suggest treatment options and design a personalized medication plan for patients.
Industrial and Manufacturing
- Suggest product design options based on material, cost, functionality, etc.
- Reduce product development timelines with proactive insights into material fitment, design concept development, market research, etc.
- Identify potential issues with a product’s quality through deeper analysis of the data from production lines, sensors, etc.
Media and Entertainment
- Create compelling content such as music, artwork, news stories, scripts for TV shows, and even commercials.
- Generate special effects and other visual elements.
- Restore damaged media and imperfections such as scratches from old film footage.
As CXOs navigate the complex digital landscape and evaluate the adoption of Generative AI, collaborating with key stakeholders is critical. Working closely with department heads, data scientists, and AI experts, business leaders can ensure a holistic approach to Generative AI solutions being implemented in the workplace. Communication is key and one of the primary responsibilities for senior leaders is to demystify the technology for others. This involves taking a step back to evaluate the strategic implications of Generative AI, understanding the associated risks and opportunities for industries and business models. As leaders craft a compelling narrative for the adoption of Generative AI, they must pinpoint two or three high-impact applications to explore and guide employees through a value-creating journey. This process transitions Gen AI initiatives from pilot tests to rapid scaling, ultimately integrating them into standard business operations. Additionally, senior leaders must commit to developing the necessary roles, skills, and capabilities—both for the present and future—to continuously test and learn with Generative AI and maintain a competitive edge.
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