Unlocking the Value of Generative AI for Business Leaders

The State of Generative AI

Generative AI has a potential $2.6 to $4.4 trillion economic impact, but how do leaders unlock it? Join Tom Godden, Director, AWS Enterprise Strategy, and Aamer Baig, Senior Partner at McKinsey and Co., as they discuss the current state of generative AI, and where it can take us in the future.

Generative AI Foundations

Generative AI will be transformative for every industry and line of business. Learn from executives about the importance of strong security and cloud foundations, skilling your workforce, and implementing AI responsibly.

From reducing packaging waste to democratizing data, Amazon’s unique approach to AI is helping advance and innovate on sustainability goals."

—Kara Hurst, Amazon VP of Sustainability

Generative AI is the Answer: What Was the Question?

Generative AI is not just a buzzword, but a game-changing technology on par with historical innovations like the printing press and electricity. Join AWS Enterprise Strategists Tom Godden, Phil Le-Brun, and Miriam McLemore, as they discuss how to harness the power of generative AI for value-driven outcomes.

How AWS customers and partners are using generative AI and ML

Hear from AWS customers and partners about how their organizations are thinking about and implementing Generative AI and ML.

Salesforce Uses AWS Services to Help Customers Deliver AI-Optimized Interactions at Scale
Salesforce Uses AWS Services to Help Customers Deliver AI-Optimized Interactions at Scale
Salesforce’s Data Cloud uses AWS machine learning and generative AI to build a solution that helps companies harmonize their customer data and deliver personalized experiences, all at hyperscale.
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Elevating the Patient Experience with Generative AI: Deloitte and Elevance Health
Join Jake Burns, AWS Enterprise Strategist; Amish Patel, CTO of Elevance Health; and Tejas Desai, Principal at Deloitte, in a conversation about how generative AI is shaping the future of the health care industry.
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 Intuit at AWS re:Invent 2023
Intuit's AI-Driven Strategy: AWS re:Invent 2023
Intuit is using Amazon SageMaker and Amazon Bedrock to combine cutting-edge technology with human tax-and-bookkeeping experts and deliver highly personalized customer experiences.
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Generative AI, Upskilling, and Mental Health: Leading in Cybersecurity with Marc van Zadelhoff, CEO of Devo
Generative AI, Upskilling, and Mental Health: Leading in Cybersecurity with Marc van Zadelhoff, CEO of Devo
This conversation explores how Devo is leveraging data, generative AI, and technology to enhance security operations, address the digital skills gap, and build a high-performing global team.
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How scientists are using AWS AI and ML to map the whole human brain
How Scientists are Using AWS AI and ML to Map the Whole Human Brain
A first-of-its-kind knowledge hub promises to advance treatment for brain disorders by synthesizing research at a cellular level.
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Navigating the Future of AI-Driven Marketing with Melissa Sargeant, CMO of AlphaSense
Navigating the Future of AI-Driven Marketing with Melissa Sargeant, CMO of AlphaSense
In this episode, AWS Enterprise Strategist Miriam McLemore joins Melissa Sargeant, the Chief Marketing Officer of AlphaSense, to dive deep into the world of marketing and AI.
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Transforming Customer Service with AI
Transforming Customer Service with AI
Cristina Fonseca, VP of Product in charge of AI/ML at Zendesk, shares insights on the optimal implementation of AI in customer experience, underscoring the importance of striking a balance between automation and human interaction.
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Delivering Innovative Health with Generative AI Solutions at Merck
Delivering Innovative Health with Generative AI Solutions at Merck
Merck & Co., Inc. (Merck), a global pharmaceutical company with an over 130-year history, has brought hope to humanity through the development of important medicines and vaccines.
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Amazon Bedrock:

>> The easiest way to build and scale generative AI applications with foundation mode.

Amazon Q:

>> A generative AI–powered assistant designed for work that can be tailored to your business.

Amazon SageMaker:

>> Build, train, and deploy machine learning models for any use case with fully managed infrastructure, tools, and workflows.

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Frequently Asked Questions about Generative AI and Machine Learning

Q. What do CEOs need to know about generative AI?

Generative AI is transforming the business world by injecting a new level of intelligence and creativity into everything from daily operations to strategic planning. It's essential for CEOs and all leadership to grasp its potential, implications, and the necessary considerations to implement it in an effective way.

Generative AI models are trained on vast datasets, enabling them to generate coherent, contextually relevant outputs that range from text to design patterns. They can predict potential outcomes and even create human-like conversations and responses.

Operational efficiency is a primary advantage of this technology. Generative AI can automate tasks like content creation, data analysis, and customer interaction, optimizing performance and freeing up employees for other tasks in the process.

Innovation-wise, generative AI offers unique opportunities. Its ability to distill from complex data can offer fresh insights, assisting CEOs in creating more informed strategies on virtually any topic. This new level of predictive analysis can reveal trends and patterns that may have otherwise been undiscovered or overlooked.

Furthermore, generative AI can significantly enhance customer experiences by powering chatbots to deliver a personalized, efficient customer interface without overtaxing employee resources or bandwidth.

It’s important to note that as generative AI evolves, CEOs should seek to acknowledge and address the many ethical considerations, data privacy issues, and potential for misuse by implementing strong governance frameworks and controls. Read our InfoBrief on Putting responsible AI into Practice.


Q. How does generative AI benefit businesses?

Generative AI delivers unique benefits to businesses, fundamentally transforming aspects like operational efficiency, decision-making, and customer engagement:

  • Operational Efficiency: Generative AI can automate business processes such as content generation and customer support, leading to improved productivity. By handling repetitive tasks, generative AI frees up employee resources for strategic initiatives, helping to streamlining operations while improving overall efficiency.
  • Decision-making: Generative AI's prowess in predictive analysis offers businesses a powerful tool for more confident decision-making. By sifting through complex data sets, it can identify patterns and trends that are often beyond human capabilities. This allows businesses to make more proactive, data-driven decisions, enhancing strategic planning and fostering innovation.
  • Customer Engagement: Generative AI can enhance the customer experience by empowering AI-powered chatbots that offer personalized interaction and troubleshooting.
  • Innovation and Upskilling: Much like how AWS Developer Center provides resources for innovation, generative AI can stimulate creativity, offering unique insights and predictive models that inspire new solutions. It also encourages a culture of continuous learning and upskilling, which is critical in a fast-evolving tech landscape.
  • Cost Efficiency: By automating certain processes and reducing dependence on manual work, generative AI can lead to significant cost savings in the long run.

Q. How can organizations prepare for generative AI?

Preparing for generative AI is a pivotal step for organizations seeking to leverage the capabilities of this transformative technology. That said, this preparation requires a strategic and carefully planned approach.

Your organization should consider these steps to prepare to implement generative AI:

  • Understanding the technology: Organizations must first grasp what generative AI is and the specific ways it can serve their unique business objectives. Engaging with AI experts, attending workshops, or utilizing platforms like the AWS Developer Center can further deepen understanding.
  • Assessing needs and goals: Defining clear goals for implementing generative AI is crucial. Whether it's enhancing customer service through AI-driven chatbots or automating content creation, setting specific targets helps in selecting the right tools and models.
  • Investing in infrastructure and skills: A robust tech infrastructure that supports AI models and data trust is essential. Cloud solutions, like those offered by AWS, can be vital in this phase. Additionally, investing in employee training to develop relevant skills can foster an environment that’s ready to leverage generative AI's capabilities.
  • Compliance and ethical considerations: Establishing guidelines for ethical usage, privacy, and compliance with regulations must not be overlooked. This involves creating policies and frameworks that govern data handling and model deployment. Read more about considerations for Responsible AI in the generative era.
  • Pilot testing and iteration: Before full-scale implementation, running pilot projects helps in identifying potential challenges and areas for improvement. Continuous monitoring and iteration ensure that the system aligns with organizational goals.
  • Embracing a culture of innovation: Encouraging technological innovation on a cultural level can ensure a smoother transition—allowing employees space to experiment and innovate with new tools.