AI Business Impact
Combined Session
Thursday, June 06, 2024 12:00—13:00
Location: B 05
Thursday, June 06, 2024 12:00—13:00
Location: B 05
This session will explore the influence of generative AI across various business and commercial sectors, highlighting its impact on startups, established businesses, and entire industries. The presenter will delve into how large businesses can leverage AI, particularly in customer operations, where AI-powered chatbots enhance self-service and agent effectiveness, leading to increased efficiency. Also, the potential for generative AI in marketing and sales is immense, automating content development, data utilization, and personalization to boost productivity.
On the other end of the scale, for example software engineering-focused startups, the presentation will suggest how generative AI streamlines activities, revolutionizing coding processes and work experiences. Examples of the impacts of AI in product R&D, such as its applications in market analysis, virtual design, simulations, and test preparations, can redefine traditional workflows and enhance efficiency.
Focusing on the retail industry, the presenter will also share insights on how generative AI could lead to a significant increase in annual revenues, transforming customer service, marketing, sales, and supply chain management through automation and optimization of personalized offerings.
Acknowledging the economic potential of generative AI, the presentation will also address challenges, such as external inference and adversarial attacks, emphasizing the role of human oversight for quality control and security in AI-era.
By the end of this presentation, attendees will have an expanded sense of the potential applications of AI-powered systems in a variety of business and commercial contexts. Information and insight are the fuel for business, and AI promises to supercharge how information is leveraged..
Contemporary institutions and record keeping systems using paper co-arose. Institutions created systems to track interactions with people over time, creating a form of institutional memory by using a range of paper-based technologies such as file record keeping and index card systems. Over the last 60 years, digital identity systems have emerged and continue to improve, thus accelerating the capacity of organizations to form institutional memories. Now we have the emergence of AI and machine learning that will advance this further - making super institutional memory.
This session explores a reframe of seeing digital identity systems as institutional memory and considers re-framing the question as how good we want institutional memory to be when building identity systems. This could be a resolution to the race between companies, partially driven by surveillance capitalism, to collect data and regulatory bodies imposing laws and regulations on data collection in the name of “privacy”, some of which have not adjusted for new technology. These two drives are inherently in tension with each other.
Asking "how good should institutional memory be'' transcends these two different drives and shifts the challenge of data collection out of a "corporate alone" decision or responsibility. It also invites a broader conversation with the public who interact with institutions and policy makers that regulate them. The answers to this question may be different for different types of institutions, but they can create new norms that bring different sides together to figure out how things should work and understand trade-offs and limits in new technologies such as decentralized identity.
Cybersecurity, biometrics & human-centered AI are shaping the futuristic automotive user journey. This talk will explore the latest trends in automotive cybersecurity, how biometrics can enhance security and convenience, how human-centered AI can create more personalized driving experiences, and the interconnected, intelligent, and autonomous vehicles of the future.
