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The data dividend: scaling and accelerating the impact of AI with trusted data

AI is as important a challenge to organisations and society as computing was in the 1970s: those who failed to harness the technology didn’t survive. So how can firms adopt AI to improve current operations or devise new services and business models?

 

For most companies, they are still developing the building blocks by collecting, storing and sharing troves of data, and analysing it with advanced analytics and big data techniques—important technologies on the path to AI. The potential benefits are huge. 

 

Generative AI is going from consumer internet applications to the enterprise. Digital twin technologies and intelligent document processing can improve organisations’ predictive abilities and productivity.

 

However businesses must address a range of operational and governance concerns. AI answers are prone to biases that can lead to misguided approaches and strategies. And to train the models, adding more computing power and energy consumption comes at a cost to companies and the environment.

 

To ensure effective AI adoption, organisations must establish guardrails for data quality and transparency, eliminate potential biases, monitor model performance and strive to ensure that AI outputs can be explained. Commitments from leading AI companies to uphold safety, governance and trust set the tone for responsible development in the private sector. How else can companies develop beneficial AI systems? What role should standards play alongside regulation?

 

This extension of the Data Dividend series, programmed by Economist Impact and supported by IBM, brings together pioneers in government and industry to discuss the value of AI for business, public services and other sectors. Discussions will focus on AI applications and data inputs, AI governance, and the risks and opportunities in AI adoption at scale.

 

The event explores vital topics:

 

  • How can technology leaders use AI to create a competitive edge for their organisations? What are the most promising, unexplored opportunities?
  • What are the main concerns for data and analytics leaders in 2023? What challenges do they face?
  • How should companies scale up their data-centric AI development? What are the conditions for building trustworthy AI?
  • How are companies managing the emergence of generative AI tools?
  • How is generative AI augmenting the workforce—and what is the role of humans? How do people’s skills need to change?
  • How may the regulation of data and AI evolve?

Who should attend?

  • Chief: data, digital, analytics, risk, compliance, privacy, customer experience, governance, technology, marketing, finance and information officers
  • VPs, Heads and Managers of: data scientists, data engineers, data architects, data analytics, data security customer and client relations, head of risk management, AI, machine learning, data management

Venue

etc.venues 360 Madison Ave, New York, NY 10017

The data dividend - an event series 

Data is an asset and differentiator in a competitive market and world filled with disruption, uncertainty and change. As digitalisation gathers pace, pioneering companies are using data as an essential resource to seize opportunities, optimise operations and create new revenue streams. Using data as a creative compass has become a foundation for anticipating and responding to new challenges, generating value, adapting to changing customer needs and improving time to market. A robust data strategy aligned with the overall business can open new sources of competitive advantage, allowing enterprises to distinguish themselves, enlist the best talent, identify risks and opportunities, and make smarter, better-informed decisions during times of economic change.