Economic Impact of Generative AI Technologies on the Tech Industry
Girish Joshi, Vice President, Ascendion, 0
In an interaction with CEOInsights India, Girish discusses the economic impact of Generative AI on tech, strategies for its effective use, policy considerations, R&D priorities, and the tech industry's role in shaping AI regulations, emphasizing the need for caution, ethics, and collaboration. Below are the key extracts from the exclusive interview –
Throw some light on the economic impact of Generative AI on the tech industry.
Generative AI is expected to contribute $1-3 trillion annually to the global economy once matures, with implications for various sectors. Currently, largely in the experimentation phase, it is set to impact, not only the software and solutions sector, but also drive growth in infrastructure, computing, and new AI chipset market. However, this impact is contingent upon factors such as ethical & regulatory alignment, data security handling, transparency, and fair implementation. Caution should be exercised to navigate these challenges.
Suggest a few effective strategies to reap maximum benefits from Generative AI technologies.
Enabling businesses to harness Generative AI's potential while managing costs effectively requires a strategic approach. Caution must be exercised in the assessment and alignment of AI strategies with business needs. Developing a clear AI strategy and establishing technology partnerships are essential. Execute a few pilot projects for viability and cost-effectiveness and be mindful of the potential risks and ethical implications. Invest in talent development on Generative AI technologies as the technology is still evolving and expertise is in scarcity.
A business use case driven approach is best suited for Generative AI technologies. Emphasis must be given to the right data selection, data quality, robust data infrastructure, choosing the right AI model and rich user experience for Generative AI projects. The integrated approach encompassing business use case, data, AI infrastructure, AI model selection, user experience and integration are necessary for successful implementations. Monitor the ongoing development of Generative AI technology till technology reaches its maturity. Adopt an open and flexible mindset for Generative AI but be mindful of the regulatory, security, and ethical alignment.
What policy implications should the tech industry collectively address to ensure responsible and efficient integration of Generative AI technologies?
The responsible integration of Generative AI into various sectors requires collective efforts from the tech industry and policymakers. While policy implications include ethical guidelines, data privacy, transparency, and bias mitigation, caution is paramount. Rushing into AI deployment without considering ethical and regulatory aspects can result in unforeseen consequences. Thus, a measured and cautious approach is necessary to ensure responsible integration.
Policy implications that the tech industry should collectively address include Ethical Guidelines & Standards, Data Privacy & Security, Transparency & Accountability, Bias & Fairness, Regulatory Frameworks, International Cooperation, Responsible AI Research, AI
Safety Protocols, Environmental Sustainability, Antitrust & Competition and Consumer Protection. By addressing these policy implications collectively, the tech industry can contribute to the responsible and efficient integration of Generative AI technologies into various sectors, benefiting society while minimizing potential risks and challenges.
As AI continues to evolve, what should the tech industry prioritize in R&D to stay ahead in today’s competitive environment?
To maintain a competitive edge, the tech industry should prioritize key areas for R&D including Ethical AI Practices, Explainable AI (XAI), AI Safety & Security, Bias Mitigation, UX Personalization, Cybersecurity, Interdisciplinary Collaboration, and Personal Data Control. Innovations in AI hardware, such as AI accelerators and quantum computing, will support more powerful and energy-efficient AI models. Additionally, investing in AI ethics research to address the complex ethical and societal challenges posed by AI will foster responsible AI development and deployment. Lastly, investing in AI education and training programs is essential to ensure a skilled workforce capable of effectively leveraging AI technologies. By focusing on these R&D areas collectively, the tech industry can remain at the forefront of AI innovation, drive economic growth, and address critical societal and environmental challenges.
Explain the role of technology companies in shaping global standards and regulations for AI technologies.
The tech industry plays a pivotal role in shaping global standards and regulations for AI technologies, especially concerning issues like privacy, security, and ethics. Tech companies can take a leadership role in developing and promoting best practices for AI development and deployment. Industry leaders should collaborate closely with governments and regulatory bodies to provide input and expertise in the formulation of AI regulations. They also can voluntarily embrace transparency by openly sharing information about their AI algorithms and contribute to education & training programs for AI ethics and responsible AI development. Establishing internal ethical review boards within tech companies can help evaluate the ethical implications of AI projects and ensure compliance with ethical guidelines and regulations. Other ways in which tech companies can contribute to this regard are through public-private partnerships, AI impact assessments, global collaboration, public transparency reports, open-source initiatives, cross-industry collaboration, and cybersecurity collaboration.
To summarize, the tech industry’s role in shaping global standards and regulations for AI technologies is crucial. By proactively addressing privacy, security & ethics concerns, collaborating with regulators & stakeholders, and leading by example in responsible AI practices, tech companies can contribute to the development of a regulatory framework that promotes the responsible and beneficial use of AI on a global scale.
How Ascendion is adapting to Generative AI technologies internally and helping its clients?
At Ascendion, we have taken a very pragmatic approach towards adapting Generative AI. Ascendion uses AI-powered software to unlock digital economy value. We are already integrating AI and Generative AI into every facet of our operations, helping us serve clients with higher levels of software quality, productivity, and insight from data. With our proprietary frameworks and platforms such as Pathfinder, A.AVA, GAIN, we are helping clients assess and refine their AI strategies, develop, and review models including large language models (LLM), build tailored Generative AI solutions, develop proof of concepts, pilot projects and help in scaling the Generative AI capabilities for customers.
As AI continues to evolve, what should the tech industry prioritize in R&D to stay ahead in today’s competitive environment?
To maintain a competitive edge, the tech industry should prioritize key areas for R&D including Ethical AI Practices, Explainable AI (XAI), AI Safety & Security, Bias Mitigation, UX Personalization, Cybersecurity, Interdisciplinary Collaboration, and Personal Data Control. Innovations in AI hardware, such as AI accelerators and quantum computing, will support more powerful and energy-efficient AI models. Additionally, investing in AI ethics research to address the complex ethical and societal challenges posed by AI will foster responsible AI development and deployment. Lastly, investing in AI education and training programs is essential to ensure a skilled workforce capable of effectively leveraging AI technologies. By focusing on these R&D areas collectively, the tech industry can remain at the forefront of AI innovation, drive economic growth, and address critical societal and environmental challenges.
Enabling businesses to leverage the full potential of Generative AI while managing costs effectively requires a strategic approach.
Explain the role of technology companies in shaping global standards and regulations for AI technologies.
The tech industry plays a pivotal role in shaping global standards and regulations for AI technologies, especially concerning issues like privacy, security, and ethics. Tech companies can take a leadership role in developing and promoting best practices for AI development and deployment. Industry leaders should collaborate closely with governments and regulatory bodies to provide input and expertise in the formulation of AI regulations. They also can voluntarily embrace transparency by openly sharing information about their AI algorithms and contribute to education & training programs for AI ethics and responsible AI development. Establishing internal ethical review boards within tech companies can help evaluate the ethical implications of AI projects and ensure compliance with ethical guidelines and regulations. Other ways in which tech companies can contribute to this regard are through public-private partnerships, AI impact assessments, global collaboration, public transparency reports, open-source initiatives, cross-industry collaboration, and cybersecurity collaboration.
To summarize, the tech industry’s role in shaping global standards and regulations for AI technologies is crucial. By proactively addressing privacy, security & ethics concerns, collaborating with regulators & stakeholders, and leading by example in responsible AI practices, tech companies can contribute to the development of a regulatory framework that promotes the responsible and beneficial use of AI on a global scale.
How Ascendion is adapting to Generative AI technologies internally and helping its clients?
At Ascendion, we have taken a very pragmatic approach towards adapting Generative AI. Ascendion uses AI-powered software to unlock digital economy value. We are already integrating AI and Generative AI into every facet of our operations, helping us serve clients with higher levels of software quality, productivity, and insight from data. With our proprietary frameworks and platforms such as Pathfinder, A.AVA, GAIN, we are helping clients assess and refine their AI strategies, develop, and review models including large language models (LLM), build tailored Generative AI solutions, develop proof of concepts, pilot projects and help in scaling the Generative AI capabilities for customers.