
AI Impact Summit 2025: Editors Recap 5 Main Takeaways of Event
Newsweek AI is in beta. Translations may contain inaccuracies—please refer to the original content.
There is no doubt that artificial intelligence is going to impact every industry worldwide. During Newsweek's AI Impact Summit in Sonoma, California, leaders from various businesses gathered to better understand AI use cases and the best ways to implement, govern and scale AI tools.
Day three of the summit had the shortest programming, but it offered some of the most important insights gathered from the entire event.
To close out, Newsweek's Editorial Director of Nexus Gabriel Snyder and contributing editor Marcus Weldon shared the five main takeaways they learned from the panels and discussions over the last three days.
AI Puts a Premium on Curiosity and Automates the Mundane
"So one example for this one was our entertainment panel and how the filmmakers are using AI to automate the mundane development process and create more quickly," Snyder said.
Weldon also added that in the health care panels, conversations explored how drug discovery and clinicians can explore pathways to come up with new treatment plans.
Sonoma, CA - Newsweek's Marcus Weldon and Gabriel Snyder present their top five takeaways from the AI Impact Summit at Fairmont Sonoma Mission Inn and Spa on Wednesday, June 25, 2025.
Sonoma, CA - Newsweek's Marcus Weldon and Gabriel Snyder present their top five takeaways from the AI Impact Summit at Fairmont Sonoma Mission Inn and Spa on Wednesday, June 25, 2025.
NICK OTTO
AI Has to Humanize Health Care and Personalize Engagement in General
"Not only were many of the health care panelists talking about how ambient scribes and other AI tools were letting doctors be with their patients and bringing back the human touch into health care. But we also heard that from the representatives from Denver and Charlotte and how they're using AI to make city services more humanized," Snyder said.
"And I think that's really interesting balance. When we think of AI, we think of it as a machine. It obviously is, but it's often by doing those mundane tasks and that we talked about first, it's opening up more space and energy for things that are uniquely human. And I think that's a really critical thing to keep in mind with all of these applications."
Instacart's Daniel Danker spoke during his panel Tuesday about personalizing the shopping experience to take the cognitive load off users to start planning not only shopping lists but meal plans.
In a Wednesday panel, Sears KAIros CEO Srini Kandala said call centers using AI agents have better access to materials to provide better recommendations for customers.
AI Has the Power to Democratize Expertise and Also Value Unique Human Expertise
"So there's a danger in that democratizing expertise, that it means that everyone will think of themselves as an equivalent expert," Weldon said. "I think it raises the foundational level."
He said the average level of knowledge is going up by interaction with these systems and, on top of that, the unique human creativity remains because we understand the world in a certain way that can't be replicated by machines.
Synder added that the "critical ingredient" for problem solving is always going to be the human expertise, saying – "there is no substitute for that."
Sonoma, CA - Newsweek's Marcus Weldon and Gabriel Snyder present their top five takeaways from the AI Impact Summit at Fairmont Sonoma Mission Inn and Spa on Wednesday, June 25, 2025. This marked the end...
Sonoma, CA - Newsweek's Marcus Weldon and Gabriel Snyder present their top five takeaways from the AI Impact Summit at Fairmont Sonoma Mission Inn and Spa on Wednesday, June 25, 2025. This marked the end of the 2025 Summit. More
NICK OTTO
AI Adoption Should Focus on the End-to-end Value Created; Efficiency and Cost Savings Are Byproducts
Snyder said this theme came up several times during the summit, including in the return on investment discussion that morning.
"I think the thing that I really learned here was the importance of always thinking about the accuracy of and the measurement of these tools, that these are not investments that you set and forget, that there is an active element of making sure that they're doing what you're expecting, that you're catching the things that it shouldn't be doing and that that element is as important as whatever you're doing on the front end to build," he said.
Weldon added that most people agree that efficiency and cost savings will happen, but shouldn't be the goal. The goal should be about value creation.
In the panel with Oklahoma CTO Rob Teel and Banjamin Maxim, the chief innovation officer at Michigan State University Federal Credit Union, the panelists stressed the importance of focusing on the "why" we are doing something and then executing "how" in order to drive efficiencies.
Responsible AI Is About Transparency and Privacy But Also Continuous Validation and Verification
Weldon said transparency means many things when dealing with AI tools: It means disclosing what the data is based on, announcing the presence of AI, protecting privacy and continuous validation and verification.
"For everything we generate, we need to validate," he said. "So this idea of constantly testing, evaluating, verifying that the answer is valid, which is a form of transparency, and then bounding that for each personalized context."
Sonoma, CA - Michigan State University Federal Credit Union CIO Benjamin Maxim and State of Oklahoma CTO Rob Teel speak with Newsweek contributor Chuck Martin in the "Navigating the Regulatory Maze: Enhancing AI Governance, Privacy...
Sonoma, CA - Michigan State University Federal Credit Union CIO Benjamin Maxim and State of Oklahoma CTO Rob Teel speak with Newsweek contributor Chuck Martin in the "Navigating the Regulatory Maze: Enhancing AI Governance, Privacy and Cybersecurity" panel during the AI Impact Summit at Fairmont Sonoma Mission Inn and Spa on Wednesday, June 25, 2025. More
NICK OTTO
Earlier that morning, there were three panel discussions about how to measure return on investment, measure success and ensure regulatory compliance.
Dr. Girish N. Nadkarni of Mount Sinai highlighted how AI can boost both patient and clinician experience in health systems – increasing returns for follow-up care for patients and decreasing burnout that will lead to greater employee retention.
With these great improvements to operations, Nadkarni did note that there should be measures for ROI and safety and ethical standards.
"I truly believe we are going to get to a point in health care where AI is going to become a part of the care team and not using AI will open up liability," he said. "I think there is something to be said about the health system that wants to use AI in a safe, effective, ethical and responsible manner."
Sachi Desai from Climate talked about using automation to help farmers with crop growth, while Maxim and Teel shared how they are each working with partners in both the public and private sectors to innovate and comply with necessary regulations.
Newsweek will host the New Destinations Summit in London on July 3 and the Women's Global Impact Forum at the office in New York City on August 5. To learn more about Newsweek's upcoming programming, visit the Events page here.

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Bloomberg
an hour ago
- Bloomberg
Kingsoft Cloud CFO on China AI Trends
Bloomberg Insight Henry He, CFO at Kingsoft Cloud, discusses the trends and opportunities with AI in China. He speaks with Bloomberg's Stephen Engle on the sidelines of the World Economic Forum in Tianjin. (Source: Bloomberg)
Yahoo
an hour ago
- Yahoo
AI-powered chat summaries are coming to WhatsApp
Meta is adding a new Message Summaries feature to WhatsApp that uses AI to summarize unread messages in a few bullet points. The feature is built on the Private Processing technique Meta announced at Llamacon in April, and claims to let AI work with content in WhatsApp without exposing any of it to Meta itself. Once the feature appears in your app, you just tap on the onscreen banner over your unread messages with that says "Summarize privately" to receive a summary from Meta AI. The Message Summaries feature is rolling out to WhatsApp users in the US chatting in English first, but Meta says it hopes to "bring it to other languages and countries later this year." The company pitches summaries as an easier way to catch-up on what you missed if you haven't checked your phone or you're just in too many chats. AI is by no means foolproof at even simple tasks like this — Apple's trouble with notification summaries was only a few months ago — but the tool could be appealing to people in particularly large and active chats. The real novelty of the summaries is how Meta claims to be deploying them without walking back the private nature of WhatsApp chats. The company has a blog post and whitepaper digging into the details of how Private Processing works, but on first blush it sounds similar to Private Cloud Compute, the method Apple uses to call on more demanding AI features without exposing its users' data. Using end-to-end encryption and a secure cloud environment, WhatsApp messages can be processed without data being accessed while its happening, or saved after the fact. Importantly, all of this is still optional. Summaries won't be provided without you asking for them first, and the feature is disabled by default. Meta also says you can exclude chats from being shared with the company's AI via the Advanced Chat Privacy feature.


Forbes
an hour ago
- Forbes
Key Tech Firms Unite As Google Donates A2A To Linux Foundation
Neurons Major technology vendors are converging around a single protocol for artificial intelligence agent communication, potentially ending the fragmentation that has limited the deployment of enterprise AI. Google's donation of its Agent2Agent protocol to the Linux Foundation brings together Amazon Web Services, Cisco, Microsoft, Salesforce, SAP and ServiceNow as foundational members of a new standardization effort. The move addresses a fundamental challenge facing enterprise technology leaders: how to deploy AI agents that can work together across different platforms without requiring custom integrations for each vendor relationship. Current enterprise AI implementations often create isolated systems that cannot share information or coordinate tasks, limiting the automation potential that drives AI investment decisions. Technical Foundation Enables Cross-Platform Agent Communication The a2a protocol operates as a communication layer that allows AI agents to discover each other's capabilities, exchange information securely and coordinate complex tasks regardless of their underlying technology stack. The system uses JSON-RPC 2.0 over HTTP for standardized communication, with server-sent events enabling real-time streaming interactions between agents. Agent discovery occurs through 'Agent Cards,' which serve as digital business cards that contain capability descriptions and connection information. When an agent needs to complete a task requiring specialized expertise, it can query available agents, review their capabilities and establish secure communication channels without human intervention. The protocol supports both synchronous request-response patterns and asynchronous workflows, accommodating enterprise scenarios where tasks may require human approval or extend across multiple business days. Authentication mechanisms ensure that only authorized agents can access specific capabilities while maintaining audit trails for compliance requirements. Amazon Web Services has already demonstrated practical implementation by creating tools that expose Bedrock agents through a2a endpoints. This enables enterprises using AWS infrastructure to make their AI agents accessible to agents running on other platforms, thereby creating the interoperability that enterprise architectures require. Market Convergence Accelerates Standards Adoption The Linux Foundation announcement represents the consolidation of previously competing approaches to agent interoperability. More than 100 technology companies now support the a2a protocol, expanding from the initial 50 partners when Google first launched the specification in April. Microsoft has integrated a2a support into Azure AI Foundry and enabled a2a agent invocation through Copilot Studio. This integration allows enterprises already committed to Microsoft's AI toolchain to participate in multi-vendor agent workflows without replacing existing investments. Salesforce contributed the Agent Card concept that became central to a2a's capability discovery mechanism. The company positions agent interoperability as essential for reaching what it terms 'Level 4 multi-agent orchestration,' where specialized agents collaborate across enterprise systems. The convergence creates particular implications for Cisco's AGNTCY initiative, which has been developing infrastructure for what it calls the 'Internet of Agents'. Rather than competing with a2a, Cisco is integrating a2a support directly into AGNTCY's core components including the Directory, Identity, SLIM Messaging and Observability frameworks. This approach transforms AGNTCY from a potential competing standard into complementary infrastructure that enhances a2a's capabilities. Strategic Implications for Technology Decision Makers The Linux Foundation's governance model offers vendor neutrality, addressing enterprise concerns about being locked into proprietary ecosystems. Technology leaders can invest in a2a implementations with confidence that the protocol will evolve through community input rather than single-vendor control. Standardization creates opportunities for enterprises to implement modular AI strategies, where specialized agents from different vendors can collaborate on complex workflows. For example, a customer service workflow might combine Salesforce agents for CRM interactions, ServiceNow agents for incident management and AWS agents for data analysis, all coordinating through a2a protocols. However, successful implementation requires careful architectural planning. Enterprises need to establish agent governance frameworks, implement monitoring capabilities and develop policies for inter-agent data sharing before deploying production systems. The protocol provides the technical foundation, but organizational readiness determines success. Technology leaders should evaluate their current integration capabilities and security postures before committing to multi-agent architectures. While a2a reduces technical barriers to agent interoperability, it does not eliminate the need for robust data governance, identity management and compliance frameworks that enterprise AI deployments require.