Results

AWS launches Amazon Quick Suite, aims to automate business workflows

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Amazon Web Services launched Amazon Quick Suite, which combines Amazon Q Business features with Amazon Quick Sight as well as new capabilities for automation and research in a move to bolster business user and AI agent collaboration.

The platform is designed to bridge the gap between AI proof-of-concepts and production deployments. In many ways, Amazon Quick Suite reflects the current playbook for AWS. AWS has been combining building blocks into suites and unified platforms that are easier to consume.

See: The AWS AI Strategy: Playing the Long Game Infrastructure-Style

Amazon Quick Suite includes these primary functions and features:

  • Information gathering from multiple enterprise unstructured data stores with connectors to Amazon S3, SharePoint, Exchange, Google Drive and others. Data is shared via APIs and Model Context Protocol (MCP). Amazon Quick Suite also leverages structured data from CRM, ticketing systems and other enterprise systems.
  • Hypothesis testing with specialized data sets.
  • Decision automation via repeatable workflows, or what AWS calls Flows, which is aimed at business users to automate routine tasks. Amazon Quick Suite also includes Quick Automate, which enables technical teams to handle complex, multi-agent, mission-critical processes.
  • A user interface agent to help business users stitch together agents and orchestrate them. UI Agent is a part of Quick Automate and Flows and can be used to interact across websites and business apps.
  • A built-in research agent that can produce comprehensive reports with verified sources and analytics on business strategy, pricing and market analysis across any industry.
  • All of the business intelligence capabilities of Quick Sight including dashboards and reports that can be created and queried with natural language.
  • Monitoring, logging and observability so admins have visibility into workflows and AI agents.
  • The ability to use multiple models via Amazon Bedrock. For default tools like built-in agent and chat agent, AWS steers users to models based on high quality responses. Model flexibility is available in Flows, where users can adjust settings for speed, comprehensive responses and deep reasoning. In Quick Automate, customers have full control and can set up their own Bedrock connector and select any model. API connectors can connect to non-Bedrock models and agents on and off AWS with MCP servers.

In a demo, Amazon Quick Suite was able to pull insights and recommend workflows across five to six enterprise systems in about 5 minutes. That output generally saved 30 minutes to 45 minutes to complete without Amazon Quick Suite or manual operations.

According to AWS, Amazon Quick Suite is designed specifically for business users with the ability to create workflows with natural language, pre-built integrations and a browser extension to meet customers where they work. Amazon Quick Suite is a horizontal approach to AI agents as AWS leverages its hyperscale cloud footprint to work across various enterprise applications and data stores.

"At a high level, we're empowering every business user regardless of technical skill and experience with generative AI to make better decisions faster," said John Brock, Head of Product, Apps and Automation AWS Agentic AI. "We also want to enable them to take action directly where they are working without having to switch between different tools."

Some of the prebuilt integrations include:

  • Atlassian.
  • Asana.
  • SAP.
  • ServiceNow.
  • Salesforce.
  • Microsoft Outlook, Teams.
  • HubSpot.
  • Marketo.
  • Microsoft SharePoint, OneDrive, Google Drive and Amazon S3 storage and collaboration.
  • OpenAI Specification.
  • Amazon Athena, Redshift and DynamoDB.
  • Slack and email.

Amazon Quick Suite supports API actions, MCP connectors, integration with existing enterprise systems and connections to agents.

With pricing of $20 per business user a month at professional scale, Amazon Quick Suite is priced on par with plans for large language model chat tools and brings together structured and unstructured data with context. Amazon Quick Suite will run $40 per user per month for a power user who would conduct a lot of research volume and build complex dashboards and technical automations.

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Google Cloud launches Gemini Enterprise, eyes agentic AI orchestration

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Google Cloud launched Gemini Enterprise, an agentic AI platform that includes Gemini models, first and third party agents and orchestration technology that was previously known as Agentspace.

The goal of Gemini Enterprise is to create one platform that can create multi-step and process AI agents coupled with the latest models and an enterprise's data. The agents within Gemini Enterprise can leverage data from internal systems and Google AI tools in one workflow.

Gemini Enterprise lands as enterprise vendors are scrambling to provide platforms that can address agentic AI workflows. Salesforce will make its case for Agentforce as a multi-agent enterprise platform. ServiceNow has a similar argument. AWS has AgentCore. Meanwhile, Boomi, UiPath and others are positioned as AI agent orchestrators.

Google Cloud said Gemini Enterprise use cases include marketing, sales and account intelligence, automated testing and code generation, HR and financial process optimization.

In a blog post, Google Cloud CEO Thomas Kurian said that the first generation of AI deployments was hampered by silos that limited orchestration. Google Enterprise provides an integrated stack that can work across processes, workflows and enterprise systems.

"Gemini Enterprise moves beyond simple tasks to automate entire workflows and drive smarter business outcomes," said Kurian, who said that enterprises need a single interface instead of a series of AI models and toolkits that have to be stitched together.

Gemini Enterprise starts at $30 per seat per month. The platform comes in Standard and Plus editions. Google Cloud also has Gemini Business, which starts at $21 per seat per month, and is designed for smaller businesses and teams. 

Components of Gemini Enterprise include:

  • Google's most advanced Gemini models and DeepMind research.
  • A no-code workbench that can be used by multiple corporate functions to orchestrate agents and automate processes.
  • A series of pre-built Google agents for specialized jobs.
  • Connectors to corporate data that resides in Google Workspace, Microsoft 365, Salesforce and SAP among others.
  • A central governance framework to audit agents.
  • An ecosystem of more than 100,000 partners.

Google Cloud cited Banco BV, Harvey, Macquarie Bank and Virgin Voyages as Google Enterprise customers. Virgin Voyages has plans to build more than 50 AI agents on Gemini Enterprise.

The strategy

Google Cloud said Gemini Enterprise has an open strategy with built-in multimodal agents designed to work within Google Workspace.

This playbook has been followed by most vendors looking to be your agent orchestration platform. The general theme for vendors is creating a platform that can work horizontally yet provide benefits if you stay with the integrated approach.

Gemini Enterprise with Google Workspace will include multi-modal agents powered by Gemini to understand text, image, video and speech. For instance, Google Enterprise is launching a Data Science Agent in preview to automate data wrangling and ingestion. Google Enterprise will be able to deliver conversational agents used in Google Cloud's Customer Engagement Suite.

In addition, Gemini Enterprise will include Gemini CLI as well as Agent2Agent Protocol, Model Context Protocol and Agent Payments Protocol to use Gemini models directly into products.

By offering seamless integration points with Google Cloud offerings, Gemini Enterprise can be differentiated.

The other side of the effort is being open enough to be a broad horizontal tool. Kurian touted Google Cloud's agentic AI ecosystem including cross-platform workflows with Box, OpenText, ServiceNow and Workday and the ability to scale with partners such as BCG, Capgemini, Infosys, Accenture, Cognizant and others.

Many of those partners are also using Google Enterprise internally.

Gemini Enterprise said the following partners will announce agents built with Gemini Enterprise: Box, Dun & Bradstreet, Manhattan Associates, OpenText, Salesforce, S&P Global, ServiceNow and Workday. Other vendors including Elastic, HubSpot and UiPath have plans to integrate agents with Gemini Enterprise.

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SoftBank's ABB robotics purchase boosts physical AI plans

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

SoftBank is acquiring the robotics division of ABB Group in a deal worth $5.375 billion. Softbank's plan is to combine ABB Robotics with its physical AI assets.

With the move, SoftBank has a base of robotics customers and manufactures to expand its physical AI ambitions. ABB will complement SoftBank’s robotics stable of companies: SoftBank Robotics Group Corp., Berkshire Grey, Inc., AutoStore Holdings Ltd., Agile Robots SE, and Skild AI.

SoftBank said that it will create a new holding company focused on its robotics businesses.

ABB was planning to spin off its robotics division. The deal is expected to close in mid- to late-2026.

SoftBank Group CEO Masayoshi Son said ABB Robotics will speed up its physical AI ambitions. "SoftBank’s next frontier is Physical AI. Together with ABB Robotics, we will unite world-class technology and talent under our shared vision to fuse Artificial Super Intelligence and robotics —driving a groundbreaking evolution that will propel humanity forward," said Son.

ABB Robotics has 7,000 workers and 2024 revenue of $2.3 billion, or 7% of ABB Group's total revenue.

In a statement, SoftBank said its mission is "actively investing and expanding its businesses in four essential areas: (i) AI chips, (ii) AI robots, (iii) AI data centers, and (iv) energy, as well as investing in companies at the forefront of generative AI."

 

Data to Decisions Future of Work Chief Information Officer

DeepSeek's launch set off China's AI boom

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

DeepSeek created an AI boom in China and has more than doubled usage as it attracts new users and then holds them, according to a research report from Microsoft Research.

In a paper, Microsoft Research took anonymized telemetry data on how people are using AI globally. The data complements other use case data from LLM providers like OpenAI and Anthropic.

First, it's worth noting that Microsoft's telemetry data has its own biases, but is a solid data set on usage. Microsoft's telemetry data is skewed toward desktop usage and the company's demographic.

In a paper, which was used in a Financial Times visual story, Microsoft researchers wrote:

"We introduce AI User Share, a novel indicator that estimates the share of each country’s working-age population actively using AI tools. Built from anonymized Microsoft telemetry and adjusted for device access and mobile scaling, this metric spans 148 economies and provides consistent, real-time insight into global AI diffusion. We find wide variation in adoption, with a strong correlation between AI User Share and GDP. High uptake is concentrated in developed economies, though usage among internet-connected populations in lower-income countries reveals substantial latent demand."

From a market share perspective, Microsoft telemetry doesn't give you any real surprises. The countries leveraging AI the most tend to be the richest.

But what really sticks out is the DeepSeek launch in January. When DeepSeek initially launched, the big takeaway is that the model from China offered a contrast to the brute force compute approach offered by the US.

After a few months, the importance of DeepSeek really revolves around putting China into the AI race. China is now the largest AI market.

Microsoft noted:

"China’s AI user share has more than doubled from 8% to 20%, making it the world’s largest AI market, with an estimated AI user base exceeding 195 million. The growth in China’s AI user population also appears to be sustained, suggesting that DeepSeek is not only attracting new users, but also keeping them engaged."

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IBM TechXChange 2025: Big blue connects agentic AI, mainframe dots, partners with Anthropic

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

IBM said its Spyre AI accelerator and Telum II processor are generally available, outlined a partnership with Anthropic and layered agentic AI tools throughout its offerings.

The news outlined at IBM's Tech Xchange 2025 in Orlando revolved around operationalizing AI in the enterprise. Here's a look at the notable news.

IBM Spyre Accelerator became generally available for IBM z17 will bring LLMs to IBM Z mainframe environment. IBM also said its software products including  IBM watsonx Assistant for Z, AI Toolkit for IBM Z and IBM LinuxONE, and Machine Learning for IBM z/OS will use Spyre for on-prem deployments.

The Spyre Accelerator has 32 AI-optimized processing cores to support LLMs on the mainframe. Combined with IBM's Telum II processor, the company said its Z platform can process up to 450 million inference operations using multiple AI models for credit card fraud detection.

IBM said it will layer Anthropic's Claude LLMs into its software portfolio starting with its latest integrated development environment (IDE). The two companies are aiming to use Claude throughout the enterprise software development lifecycle. IBM said more than 6,000 early adopters in the company are using the new IDE, which is in preview with IBM customers.

The IDE, called Project Bob, includes tools for application modernization, code generation and review and security embedded into workflows.

IBM watsonx Orchestrate gets new tools for agentic AI including workflows that are reusable and sequence multiple AI agents, Langflow integration, a catalog of prebuilt agents for procurement, HR, finance, supply chain and sales and prebuilt customer service agents.

Watsonx Orchestrate also includes agent observability, governance and production monitoring.

IBM delivered a new release of watsonx Assistant for Z to improve the mainframe user experience with a AI chatbot grounded on Z expertise.

 

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Dell Technologies ups revenue outlook due to AI infrastructure

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Dell Technologies raised its annual revenue growth target to 7% to 9% as it ramps its AI infrastructure business.

The company outlined its guidance at its security analyst meeting. Dell maintained its third quarter guidance delivered when it reported second quarter earnings.

Dell said its updated annual revenue growth will be in the 7% to 9% range, up from 3% to 4%. The company also said it will raise its dividend 10% or more annually through 2030. Annual non-GAAP earnings growth will be 15% or better.

CEO Michael Dell said, "customers are hungry for AI and the compute, storage and networking we provide to deploy intelligence at scale." He added that the AI "opportunity ahead is massive."

The company argued that it is well positioned for AI data center infrastructure as well as PCs.

In a presentation, Dell laid out the following points:

  • AI is in the early stages of adoption and traditional data centers will be key to AI deployments.

  • AI inference will support growth going forward and enterprises will increasingly go with low-cost inference at the edge and disaggregated architectures. PCs will also play a role in edge AI.

  • Traditional server and storage growth will be driven by AI workloads.

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CoreWeave acquires Monolith, eyes industrial AI use cases

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

CoreWeave said it will acquire Monolith AI Limited, which specializes in AI for engineering in industrial and manufacturing companies.

Terms of the deal weren't disclosed, but the purchase is notable because CoreWeave is looking to take its broader AI infrastructure workloads vertical where the customer base is stickier.

Indeed, Monolith has a strong customer base including BMW, Mercedes-Benz, Honda, Nissan and Siemens to name a few. Monolith's platform is used for simulation and testing for physics and engineering solutions. CoreWeave has been rounding out its business with acquisitions including OpenPipe and Weights & Biases.

With CoreWeave, Monolith will get access to an AI stack for its customers. According to CoreWeave, the combined company will give customers the ability to speed up R&D, product development and design. CoreWeave Chief Strategy Officer Brian Venturo said AI can transform manufacturing.

"Monolith was founded to put AI directly into the hands of engineers, enabling them to create breakthrough technologies. Joining CoreWeave will allow us to scale that mission dramatically," said Dr. Richard Ahlfeld, CEO of Monolith, in a statement.

Holger Mueller, an analyst at Constellation Research, said:

"This is CoreWeave's first entry into the AI applications space, and it may highlight a potential future concern on workloads. The higher in-house, organic workloads are for CoreWeave relative to volatile AI provider workloads, the more stable CoreWeave's utilization of data center capacity."

Monolith's platform embeds AI and machine learning directly into engineering workloads and reduces the need for physical testing. Here are a few screenshots of Monolith’s platform.

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OpenAI sets SDKs for app integrations, agentic AI building blocks

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

OpenAI launched App SDK, which connects applications directly to ChatGPT, AgentKit to speed up AI agent development, ChatKit to bring OpenAI to apps and websites, the general availability of Codex, and said ChatGPT-5 Pro and a smaller voice model is available in the API.

The company also said that it has 800 million weekly users, 4 million developers and 8 billion tokens processed per minute on OpenAI's API.

Speaking at OpenAI's Dev Day, CEO Sam Altman outlined the company's latest developer releases and placed the company in the middle of the software ecosystem. Demos highlighted integrations with Canva, Figma, Coursera and callouts for enterprise software vendors like HubSpot. The HubSpot mention eased concerns about OpenAI targeting SaaS directly.

Altman's keynote revolved around creating applications without code, enabling voice interfaces and using ChatGPT as an interface to third-party software vendors. Altman addressed developers directly:

"We're going to show you how we're making it possible to build apps inside of ChatGPT and how we can help you get a lot of distribution. We're going to show you how building agents is going to be much faster and better. You'll see how we're making it easier to write software. We think this is the best time in history to be a builder. It has never been faster to go from idea to product."

Key points from OpenAI's Dev Day announcements:

  • Apps SDK is in preview and Model Context Protocol (MCP) is the connective tissue between ChatGPT and applications. "With the Apps SDK, you get the full stack. You can connect your data trigger actions, render a fully interactive UI and more," said Altman. "You get full control over your back end logic and front end UI. We've published the standard so that anyone can integrate the Apps SDK. Your apps can reach hundreds of millions of ChatGPT users."

  • OpenAI will highlight partner apps built via Apps SDK. "We'll also release a directory that users can browse in addition to discovery and conversation," said Altman. For now, the launch applications for the Apps SDK are decidedly consumer.
  • The company is looking to make it easier to create AI agents. "It's hard to know where to start, what frameworks to use, and there's a lot of work. There's orchestration, eval loops, connecting tools, building a good UI, and each of these layers adds a lot of complexity before you know what's really going to work," said Altman.
  • Agent Kit will offer a set of building blocks to build, deploy and optimize agentic workflows. OpenAI said it is targeting individual developers as well as enterprise. Altman highlighted Agent Builder, a canvas to build agents, design logic steps and test workflows. Agent Builder is built on top of OpenAI's Responses API. Chat Kit will bring an embeddable ChatGPT interface. Agent Kit will also include OpenAI Connector Registry, which will provide trusted access to data and agents. There's also a control panel for administrators.
  • "Almost all new code written at OpenAI today is written by Codex users," said Altman. He said more features will be announced shortly and cited a big Codex deployment at Cisco.
  • ChatGPT-5 Pro will address use cases in industries such as finance, legal and healthcare. The smaller voice model is designed to address voice applications at a lower cost.
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HOT TAKE: Magnify.io Adds New Agentic Tools to Optimize Post-Sale Revenue Growth

Martin Schneider
Vice President and Principal Analyst Constellation Research
Martin Schneider has had a unique career that has spanned both analyst and marketing practitioner roles, focused on high technology and related industries. The unifying factor has always been both a keen analysis of go-to-market trends, while also having achieved success as a marketing leader. Schneider started his career as a journalist covering B2B technologies, and quickly transitioned into a leading analyst covering application software for the 451 Group in NYC, where he specialized in CRM, marketing automation, and business intelligence/analytics technologies. After analyzing various go-to-market strategies of dozens of technology vendors, Schneider made the move to the vendor side, where he led successful go-to-market teams for several startups and established tech providers,… Read more

Post-sales is a critical phase of the customer lifecycle in terms of offering up the most opportunities for expansion revenue and optimizing customer lifetime value. But these signals often get lost in silos or simply ignored, leading to lost revenue opportunity. To address this issue, Magnify, which bills itself as a customer growth optimization platform focused on post-sales optimization, has launched its new AI Assistant, an agent purpose-built to optimize key elements of post-sales revenue generation. According to Magnify, the new tool is designed as a proactive, intelligent agent designed to find and execute growth opportunities automatically across the customer lifecycle.

A pervasive issue in growth optimization is the continued silos of data that typically prevent the ability to identify both positive and negative customer signals. And most AI tools are still bolted on to a single system like a CRM or customer success platform, delivering limited insights. And AI analytics can often deliver complex analysis, but typically without a direct path to action. Magnify CEO Josh Crossman acknowledged this industry gap, stating, “Our industry has talked about AI for years, but it’s not delivered revenue growth and real cost-savings. With Magnify’s AI Assistant, we’re delivering something entirely different; an agent that doesn’t just analyze data, it acts on it.”

The Assistant monitors granular customer signals, autonomously forecasting outcomes, and can execute the right plays across every digital touchpoint. This agent combines GPT-powered personalization with seamless multi-platform orchestration to identify and take action on growth opportunities. Crossman likens it to “adding an analyst, data scientist, and growth marketer to the team who never sleeps, scales infinitely, and stays focused on outcomes that matter: retention, expansion, and growth.”

The Magnify AI Assistant achieves this by orchestrating three core, interlocking capabilities:

Autonomous Forecasting: Predicts churn, conversion, and expansion opportunities quarters in advance, updating in real time as customer behavior shifts. Provides drivers of churn and expansion.  See recommendations on next best steps for accounts and users. 

Universal AI Research:  Use AI to search in seconds across product, marketing, sales, and CS systems to find hidden insights like disengaged users or at-risk accounts. Ask any question to analyze entire segments, user cohorts, or individual accounts.  See insights from 

Unlock Productivity Gains with AI Automation: Trigger actions in any connected system via Magnify, automatically running multi-platform motions across all your systems. Create campaigns in minutes using AI or one-off actions for users. Automate email, in-app, messages, support, tasks, and more to engage all your users and accounts. Get rid of tedious, repetitive tasks, unlocking massive productivity gains for post-sales teams .  All personalized with GPT-quality messaging.

The Magnify agentic approach seeks to eradicate tedious, repetitive tasks, allowing post-sales organizations to focus more on revenue and expansion opportunities. By automating engagement with all users and accounts, human talent is freed up to focus on high-touch, strategic engagement, accelerating measurable post-sales revenue growth without the need to hire more staff.

For growth leaders looking to optimize post-sales growth, agentic tools can speed the reinvention of GTM motions. However, a lot of AI agents offered from CRM and customer success tools are focused on only the data inside their respective systems. And, they can increase the cost of ownership of core systems significantly. Tools like Magnify can be a strong “easy button” to pulling together data from disparate GTM apps, adding agentic flows to take action across sales, customer success and other revenue stakeholders. In this new age of AI, growth leaders need to identify the fastest paths to success, mitigating risk while improving outcomes. 

 

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Verizon names Dan Schulman CEO

Larry Dignan
Editor in Chief of Constellation Insights Constellation Research
About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Verizon named Dan Schulman CEO effective immediately. Schulman, former CEO of PayPal, is a Verizon board member and a telecommunications veteran.

Schulman replaces Hans Vestberg, who will stay with the company in an advisory role for a year. Verizon also named Mark Bertolini chairman of the board.

The leadership change comes as Verizon is transforming via the acquisition of Frontier Communications. Vestberg led Verizon through the 5G transition.

Schulman brings an interesting mix of experience to Verizon. He was CEO of PayPal, but also had leadership roles at AT&T, Priceline, Virgin Mobile and American Express.

In a statement, Schulman said:

"Verizon is at a critical juncture. We have a clear opportunity to redefine our trajectory, by growing our market share across all segments of the market, while delivering meaningful growth in our key financial metrics."

Verizon reaffirmed its outlook for 2025.

Here's a look at Schulman's experience.

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