Results

Anthropic Claude Research integrates with Google Workspace

Anthropic said its Claude large language model (LLM) will integrate with Google Workspace to add enterprise documents for its Research feature for Max, Team and Enterprise customers.

The company's Claude model has had an enterprise spin and vision that revolves around making its LLM a work partner. With its Google Workspace integration, Claude will be able to add internal documents such as email, calendar and docs.

According to Anthropic, Research is in early beta, web search is available in the US and Workspace integration is available in beta.

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Anthropic said in a blog post:

"With Research, Claude can search across both your internal work context and the web to help you make decisions and take action faster than before."

Claude will also provide inline citations to verify sources. Anthropic is betting that integration with Google Workspace will enable Claude to handle more marketing, sales, engineering and education use cases.

A few thoughts on Claude's integration with Google Workspace.

  • The integration between Claude Research and Google Workspace will enable more bakeoffs between Anthropic and Google Cloud's Gemini models.
  • Google Workspace is likely just the first Anthropic partner. Expect more partnerships with the likes of Box and other content repositories.
  • Anthropic is building a set of tools around Claude and ultimately could become more of a work collaboration platform.
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Cohere rolls out Embed 4, an enterprise multimodal search model

Cohere launched Embed 4, a multimodal embedding model that beefs up enterprise search and retrieval for AI apps.

According to Cohere, Embed 4 can quickly search unstructured data including PDF reports, presentation slide and other documents with text, images, tables and diagrams.

The launch is a fast follow-up to Command A, a model designed to minimize compute resources while delivering strong performance.

Embed 4 also can generate embeddings for documents up to 128K tokens or about 200 pages. The model is also multilingual with more than 100 languages.

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If you zoom out a bit, Cohere's moves with Embed 4 highlight a broader product strategy that revolves around enterprise use cases. For instance, Cohere said Embed 4 is "optimized with domain-specific understanding of data from regulated industries such as finance, healthcare, and manufacturing."

Cohere in January launched North, an AI platform designed for streamlining work. Cohere is also developing a version of North for banking.

The company also noted that Embed 4 can be deployed in virtual private clouds or on-premise environments. Cohere's game plan is to address enterprise retrieval augmented generation (RAG), which will be critical to deploying AI agents.

Cohere noted that Embed 4 can search unstructured documents where they reside and represent them in a unified vector. Embed 4 is available on Cohere, Microsoft Azure AI Foundry and Amazon SageMaker for virtual private cloud and on-premises deployments.

With Embed 4, Cohere is addressing multiple areas of the model stack including retrieval as well as prompt augmentation with Rerank and generation with Command A models.

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Bank of America's AI investments boost digital engagement, customer satisfaction

Bank of America is infusing AI throughout its primary units--consumer banking, global wealth and investment management and global banking and markets--and plans to spend $4 billion on new projects as its digital engagement gained throughout 2024.

The company outlined how its AI and machine learning tools, which are headlined by its Erica virtual assistant that launched in 2018, are gaining traction for multiple use cases.

Bank of America CTO and CIO Aditya Bhasan said "our use of AI at scale enables us to further enhance our capabilities, improve employee productivity and client service and drive business growth."

The bank has an annual technology budget of $13 billion and $4 billion of that sum is allocated to new AI projects in 2025. Bank of America has more than 1,200 AI and machine learning patents.

Key projects include:

  • Erica for Employees was launched in 2020 and expanded in 2023 for use cases in health benefits, payroll, tax forms and HR use cases. Erica for Employees is used by 90% of workers and has reduced calls into the IT service desk by 50%.
  • Bank of America said Erica for Employees will use generative AI to cover more topics.
  • Ask Merrill and Ask Merrill takes the technology for Erica and uses it for curate information and data and client experiences.
  • The Academy is an AI driving training platform for coaching with conversation simulators. Employees completed more than 1 million simulations in 2024 to practice client conversations.
  • AI is also being used for coding assistance, client meeting prep, optimizing call centers and research.

What sticks out for Bank of America's use cases for AI is that much of the projects are aimed at experience and driving revenue growth. The employee efficiency angle to AI was added later--partially due to the benefits of generative AI.

These efforts have enabled Bank of America to grow revenue and efficiency as well as digital interactions, which can offer better experiences at lower costs.

Bank of America, like many financial services firms, reported strong first quarter results. The company reported first quarter earnings of $7.4 billion, or 90 cents a share, on revenue of $27.4 billion, up 6% from a year ago. Bank of America added consumer and global wealth and private bank accounts of 250,000 and 7,200, respectively. Average deposits grew for the seventh consecutive quarter to nearly $2 trillion.

Going forward, here are some of the trends to watch.

Consumer Banking

  • Can Bank of America boost its digital enabled sales and to what level? In the first quarter, digital sales were 65% of the total in consumer banking.
  • Can Erica interactions largely replace human interactions?

"Digital adoption and engagement continued to improve, and customer experience scores rose to record levels, illustrating the appreciation of enhanced capabilities from these investments," said CFO Alastair Borthwick.

Global Wealth and Investment Management

Digital adoption reaches 87% of global wealth relationships. Can that tally get to nearly 100% as customers age out?

Global Banking

Digital engagement is lower for the global banking unit and may provide upside in the future.

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As tech navigates volatility, here's what the big finance CEOs say about the economy

Corporations and consumers are trying to navigate economic uncertainty and many are hitting the brakes amid tariffs, declining sentiment and volatility that's curbing long-term bets.

Those are some of the takeaways from a series of big financial earnings. These results are lead-ins to what tech giants will be talking about in the weeks ahead as they deliver first quarter results. See: After volatile first quarter, these 10 questions loom over enterprise technology, CxOs

Here's a look

A challenged economy

Morgan Stanley CEO Ted Pick said the current period of volatility, tariffs and whipsaw policies reflect the end of globalization and it's an adjustment.

"We've been talking for the last three years about the end of the end of history, which is to say the end of an extended period of political and economic alignment toward globalization. History now resumes," said Pick. "And with that comes an adjustment period where the outlook is necessarily less predictable. The stock, bond and currency markets are exhibiting the kind of overnight and intraday volatility that reflect rapidly changing probability assessments of different policy outcomes."

"The simple truth today is that we do not yet know where trade policy will settle nor do we know the actual transmission effects on the real economy," said Pick.

Blackrock CEO Laurence Fink said the market volatility can impact consumers as well as enterprises. "The market downturn impacts millions of ordinary people's retirement savings. Their investments for a child college education and tuition or steps they're taking to have more financial stability. We're in a period of geopolitical and economic activity, but we have seen this before. When there are big pivots in the world, big structural changes in the market, like the financial crisis, like, the European debt crisis or COVID or the surging inflation in 2022," said Fink.

Fink added that Blackrock's clients aren't capitulating, but they are raising cash. It's also possible that the US, which represents 75% of the world's capital markets, will become more like 50% as Europe invests in its economies."

Wells Fargo CEO Charles Scharf said: "Our current expectation that we will face continued volatility and uncertainty, and are prepared for a slower economic environment in 2025, but the actual outcome will be dependent on the results and timing of policy changes," he said.

The Bank of New York Mellon (BNY) CEO Robin Vince said the year started out with optimism about the economy in 2025, but quickly went south. "We have now seen a rapid and significant reversal of sentiment, driven by uncertainty about trade and fiscal policies, which added to existing tail risks, including a variety of geopolitical tensions and conflicts," said Vince. "I think you have to be a little bit pessimistic here about how the economy is going to evolve over the course of the next six to nine months."

Goldman Sachs CEO David Solomon said markets are likely to remain volatile:

"We are entering the second quarter with a markedly different operating environment than earlier this year. Our economists' expectation for growth in the US has fallen meaningfully from over 2% to 0.5%. The prospect of a recession has increased with growing indications that economic activity is slowing down around the world.

Our clients, including corporate CEOs and institutional investors are concerned by the significant near-term and longer-term uncertainty that has constrained their ability to make important decisions. This uncertainty around the path forward and fears over the potentially escalating effects of the trade war have created material risks to the US and global economy."

Enterprise and consumer spending uncertain

JPMorgan Chase CFO Jeremy Barnam said it's unclear where consumer spending goes. "Thing to check is the spending data. The main thing that we see there is what would appear to be a certain amount of front-loading of spending ahead of people expecting price increases from tariffs," said Barnam.

On the corporate side, Barnam said clients have been reacting to tariff policy changes. "At the margin that shifts their focus away from more strategic priorities with obvious implications for the investment banking pipeline outlook towards more short-term work, optimizing supply chains and trying to figure out how they're going to respond to the current environment," he said.

Barnam added that smaller businesses are going to struggle, and the hit to large enterprises will depend on sector and how exposed they are to tariffs. "There's certainly a bit of wait-and-see attitude," said Barnam. "It's hard to make long-term decisions right now."

Morgan Stanley's Pick said something similar and companies are putting off strategic decisions until there's more clarity about the economy.

So long, earnings guidance

JPMorgan Chase CEO Jamie Dimon said companies will likely table earnings guidance due to the uncertainty. Dimon said:

"I don't usually pay that much attention to anecdotes, but this time I am. I think you're going to hear a thousand companies report and they're not going to tell you what their guidance is. My guess is, a lot will remove it," said Dimon. "They're going to tell you what they think the uncertainty might do to their customers, their base, their earnings, their costs, their tariffs. It's different for every company."

And earnings estimates will be cut. Dimon noted that analysts have reduced earnings growth estimates for the S&P 500 by 5% from 10% already. "My guess is that'll be 0% and negative 5% probably the next month," said Dimon.

M&A and IPOs may freeze

Dimon said M&A is going into wait-and-see mode and for mid-market companies deal will stop as companies adjust to the new reality.

Pick said there's a lot of nuance in the current M&A market. "Some clients are naturally going to pause, and others are a go. There are financial sponsors buying and selling as we speak, Honeywell, Warburg Pincus, buyer. Clearlake, Dun & Bradstreet. There are sponsors buying and selling assets," said Pick, who added that deals will still happen but occur amid uncertainty that needs to be priced in.

As for IPOs, there's a parade of companies that could go public but that may move out "a quarter or two," said Pick. However, these IPOs and M&A deals aren't being paused not deleted. Pick said once the markets are stable, deals will pick up.

"Stability will be more important than valuation. Most of these transactions are of comparative value. It's a question of what your longer-term priorities are with respect to things that matter to you in the C-suite around supply chain, energy, technology and sizing against the sector. With the IPO calendar there were folks that came right as that window briefly shut. The window ought to reopen and potentially reopen for periods of time that will allow for a lot of the new parade of companies to come through."

"In investment banking, the volatile backdrop led to more muted activity relative to the levels we had expected coming into the year," said Solomon. 

Investments in AI will continue

Fink said Blackrock has expanded its AI infrastructure effort with xAI and Nvidia joining as partners. Fink said the fund has attracted "significant capital interest." "The partnership will meet the expected target of $30 billion in capital from investors, asset owners and corporations," said Fink. "And over time, we believe this can unlock over $100 billion in investment potential, including debt financing of these infrastructure projects."

Blackrock noted the volatility and uncertainty in the markets, but noted that " the mega forces like artificial intelligence, surging demand for global infrastructure and an ongoing evolution of debt financing presents transformative investment opportunities." Fink added: "Build outs of data centers and energy, the need for power grids in semiconductor plants and other infrastructure are beginning and are going to be growing dramatically over the coming years."

Even as the role of the US globally is re-evaluated the broad AI trend continues. "Eighty days ago, everyone talked about U.S. supremacy, the vitality of the United States. That is not a conversation that is happening now, but the macro forces of AI of infrastructure is just as strong today as it was 80 days ago," said Fink.

With Blackrock's Fink focusing on the macro picture for AI investment, Vince noted BNY is like many enterprises investing in the technology for efficiencies. BNY as deployed more than 40 AI tools into production, with many more in the building and testing phase and training complete for 80% of its workforce. The company also inked a deal with OpenAI to advance use cases.

"Collectively, we expect these to drive productivity gains, improved risk management and to provide meaningful leverage to our people in the future," said Vince. "We strongly believe that by empowering our people with AI to do what we do better every day, we will harness great benefits over the coming years."

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A look at Walmart’s platform approach to data, AI, optimization

Walmart's move to common platforms that work across various functions, divisions and stores is enabling a data and AI flywheel that is paying off nicely in an uncertain economy.

To Walmart CTO Suresh Kumar said these platforms enable the retail giant to leverage data for customer experience, inventory flows and automaton. At Walmart's investor meeting, the company laid out a bevy of projects that leverage generative and agentic AI. Walmart also maintained its first quarter outlook.

At a high-level Walmart detailed the following:

  • Sparky, an AI shopping assistant.
  • Trend-to-Product, a tool to speed up fashion design.
  • Just Go AI Checkout, a computer vision checkout system that will be rolled out to all Sam's Club locations.
  • Wally, an AI assistant for merchants that will evolve into an inventory AI agent.

Kumar said Walmart has a unique advantage given it serves more consumers across more physical and digital touch points.

"Walmart has got a great advantage because we serve customers in more ways than anybody else, so that means that we have many more places where we can understand both the customer and their intent. Ultimately, it's all about how effectively we can take the data, and then the models can work on the data," said Kumar. "Walmart has got a better advantage than just about anybody else, just given the fact that it's not just only about online, it's about how we saw our customers inside the store, the services, put it all together, you have a much better view from a customer perspective of what they want as well as what is the context."

Kumar also noted that Walmart has had a long history investing in AI and automation to orchestrate inventory flows, but generative AI ensures every associate has the right tools. "We believe that going forward, customer experience is going to become more personalized and contextual," said Kumar.

Internally, the focus for Walmart is on inventory and using AI to be a better predictor of demand.

The impact of leveraging platforms is clear to Walmart CEO Doug McMillon. He said:

"What Suresh and the team have done to create commonality enables us to optimize. And we weren't able to optimize before. We were by nature sub-optimizing. And when you layer AI into this entire equation, you think about improvements in forecasting and other areas, it gets really exciting to think about what's possible in the future to do a better job of predicting demand, matching it with supply and taking out all of the costs and other friction that goes along with imperfect freight flow."

Breaking down silos with horizontal platforms

Walmart executives during the investor day session repeatedly referred to platforms that use AI for multiple use cases. Consider:

  • Sam's Club CEO Chris Nicholas said the unit is leveraging Walmart's broader platforms including the fulfillment network and tech stack to expand. Using AI, Sam's Club has already eliminate 100 million tasks for associates.
  • Tom Ward, Chief Operating Officer at Sam's Club, said his team is building a seamless connection from supply chain to club to e-commerce business to last mile delivery. "These platforms were and continue to be transformational in the speed and quality of service our members and customers receive," said Ward.
  • These platforms pay off across Walmart units. "Because we're a part of Walmart, we do not have the same fixed cost burden or the long development lead time that we would have as a stand-alone operator. We are using the same tech platforms a the Walmart commerce platforms for our e-commerce app. We're utilizing the Spark driver network for deliveries, including for Express," said Ward. "We are merging supply chains with Walmart U.S. And that will help us enable two day shipping nationwide for most items over time, even in places where we don't have clubs, which means that not all members will have to live near a physical club."

John Furner, CEO and President of Walmart US, said the platform approach give the company real-time visibility into what's happening from store to supply chain. Walmart can leverage AI and data to respond to trends quickly.

Here’s a look at Walmart’s key AI projects across the company.

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AI strategies and projects: The hope, the fear and everything in between

When it comes to AI strategies and projects we've seen the hope, the fear and the reality all within a few days.

Google Cloud Next 2025 provided an interesting backdrop to the state of agentic AI, enterprise use cases and how AI is altering corporate strategies. Here's a quick tour.

The hope

Let's start with hope shall we? Google Cloud outlined how it is working with Sphere Entertainment, Magnopus and Discover Warner Bros. to bring “The Wizard of Oz” to Sphere. The mission: Revamp the 1939 classic with AI technology that was essentially being developed on the fly. The companies developed a "super resolution" tool to turn celluloid frames from 1939 into high-definition imagery using Google Cloud models, AI outpainting and models to expand the scope of screens.

Now this project could have gone terribly wrong. If the AI enhanced any of the characters so they weren't realistic or looked like animation or CGI, the audience would revolt. I've seen enough of the Sphere version of Oz to know that you won't, but you'll have to wait until August to find out.

Nevertheless, what stuck out most about the Oz project was the passion about the creative side of the equation. Google CEO Sundar Pichai said AI is about augmenting creators and giving them new tools. "Filmmaking has been and will always be a profoundly human invention," said Pichai, who said the goal was to do things that have never been done while maintaining the original spirit of the film.

Google Cloud CEO Thomas Kurian said with a project like Oz at Sphere needs to apply AI with intent and responsibility. Models had to be fine-tuned on the source material--notebooks on cameras, film and still shots--to be historically accurate.

The artistic and technical collaboration behind bringing Oz to Sphere revolves around co-creation. "The artist collaborated with the technologist and then the AI spoke back to us," said Sphere CEO Jim Dolan, who noted that he felt like a partner instead of a customer of a vendor.

Now you could argue that bringing Oz to Sphere was a unique project that is hard to replicate from a collaboration perspective. The project had passion and was almost a cause. But it's hard to miss the ideal mix of ingredients where AI amplifies human creativity, and collaboration and creativity flourish.

The fear (at least for humans)

Shopify CEO Tobias Lütke made some news with a staff memo that boiled down to the following:

  • AI usage is baseline expectation. Shopify employees all need to be using AI naturally and frequently as part of the day-to-day workflow.
  • AI isn't an option. It has to be learned and performance reviews for employees will include AI skills and usage.
  • The human hiring freeze. Teams need to demonstrate that needs can't be fulfilled by AI before requesting a hire.

Overall, Lütke said Shopify is all-in on AI and it's a cultural change. Lütke didn't say anything that other CEOs haven't said before. He was just a bit more direct about preferring AI as a force multiplier over hiring. This take shouldn't be a shocker given the steady stream of technology company layoffs in the last two years.

Lütke caught flack on social media for his memo, which was leaked so much he just posted it.

Here's why Shopify's AI approach may turn out to be a disaster. AI projects are about change management as much as technology and fear doesn't necessarily drive change over the long run.

The risk of Lütke's strategy is fairly obvious:

  • Shopify's tone with AI is urgent, but some employees will be overwhelmed and left out. Change fatigue could be real.
  • It's unclear from Lütke's memo how much training and support for this AI knowhow will come from Shopify.
  • Cultural resistance and lack of buy-in. Lütke's requirement that teams will have to justify headcount requests by proving AI can't do the job saps morale. It takes little to make the hop that AI-first means downsizing later.
  • AI usage as a performance review requirement is heavy handed and not all roles are going to be 100% AI driven.
  • Lütke's memo is likely to be a poster for how AI is going to take jobs. My hunch is that Shopify employees are going to feel like the person who had to train her replacement when a downsizing was on deck.

The in-between works in progress

I spent a good chunk of my Google Cloud Next time checking out customers adopting AI agents and generative AI. These vignettes weren’t just about productivity and included a lot of transformation.

Some high level takeaways include:

  • A general feeling of optimism about AI agents.
  • Time to value matters.
  • Google Cloud has its ground game down with its go-to-market strategy and has organized around industries.
  • The use cases for AI are almost infinite. When a vendor can put more than 600 use cases in a blog, you know you have some mojo.

We're in the early innings of what's possible with AI. "Agents are in early stages right now and starting to be proven out," said Google Cloud CTO Will Grannis. "AI agents need to scale out with authentication, stability, reliability."

Here's a look at just some of the customer stories from Google Cloud Next.

The overall vibe is that enterprises are looking to scale AI to transform their businesses.

Citigroup CTO David Griffiths said the banking giant is leveraging Google Cloud as part of its multi-year transformation. "Anywhere we work with digital transformation, AI can help. We are embracing AI as a universal enabler," said Griffiths.

Griffiths outlined the strategy:

  • "We've been guided by a couple of simple principles, with taking a very deliberate approach. We build a simple, scalable, secure, multi-model platform that has centralized controls and observability, so we can keep everyone safe, and we can learn and observe across the breadth of all of our AI interactions."
  • "We think about the impact of AI in two dimensions: General, horizontal, assistive AI tools that have very wide applicability. These may only give you 1% to 3% of productivity back, but you scale that across the company, this really adds up. And you have to complement that with deeper AI verticals, specialized capabilities for the specialists within your workforce."
  • "A scale footprint allows us to maximize the impact as this technology advances. Google is at the frontier of AI development, and we want to have a mini lag between AI innovation and AI impact."

Griffiths added that Citigroup had about 1,000 use cases in 2024 at various stages. Those use cases were horizontal and could benefit the entire organization. In 2025, Citigroup is focused on scale and depth and "industrializing our AI verticals" for customer servicing, fraud detection, finance and sales and marketing.

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Citigroup’s journey

During Kurian's keynote, Verizon was cited as a Google Cloud Customer Engagement Suite customer that has advanced over the past year. Verizon was an early customer of the Customer Engagement Suite and ramped usage over the last year.

Verizon is using a personal research assistant powered by Google Cloud to give its 28,000 care reps personalized information about a customer's needs.

The wireless giant is seeing better service, lower wait times and improving customer satisfaction scores.

Compared to Citigroup and Verizon, Pearson isn't as far along with its AI plans. Pearson CTO Dave Treat said the education and learning company is transforming to "use AI to help educators and students transform learning across all stages of life."

The company is betting on agentic AI.

"We've realized it's time for us to think outside the book, and we're really just at the beginning now of creating super effective, personalized learning experiences using agents," said Treat. "We're envisioning a team of agents working together on behalf of educators and students using natural language interfaces integrating all of the tools and resources that they need guided and shaped by our learning science and trusted content."

Treat noted that agentic AI will change its engineering and software development lifecycle. Pearson is using specialized agents for code, documentations, and testing scripts.

According to Treat, Agentspace will be the control plane for multiple agents including ones from Salesforce and ServiceNow. Treat's take highlights how hyperscalers may be best suited to orchestrate AI agents across systems. "Just like humans, there's going to be the right agent for the right job," said Treat.

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Content, Engagement and the Chaos In Between: A Case for Supply Chain Management as a Strategy to Manufacture Opportunity

Media Name: Firefly panda bear, working in a pickle factory, lots of machines packing 52795.jpg

What if you could manufacture opportunity?

This is not to ask what if you could manufacture campaigns. Instead, this is to ask if we could think about manufacturing opportunity the same way we might think about manufacturing a jar of pickles? Simply: Yes. If the ask is to manufacture opportunity for the purpose of profitable growth, a supply chain dedicated to the creation and optimization of content that acts as the fuel for engagement can and should be established.

Today, the complex web of functions, talent, tools and processes attached to content creation has left organizations with nothing less than chaos. This web is a bottleneck that brings our system to manufacture opportunity to a screeching halt.

What is Supply Chain Management, and How Does it Apply to Content?

Let’s talk about pickles. To meet market demand, you sell 100 jars each month so, you order enough cucumbers to make 100 jars for the month of June. But the lid manufacturer can only supply 90 lids for June. Without visibility and automation in the supply chain, you are still ordering ingredients, making pickles, and filling 100 jars, wasting the 10 with no lids. Making this worse, you already took orders for all 100 jars and now 10 customers are out of luck. No pickles for them.

A supply chain strategy is a plan to manage how goods and services are made and delivered. This encompasses everything from raw materials to final delivery, detailing the people, platforms and processes that are required. Supply Chain Management (SCM) typically breaks down into coordination, planning, execution, delivery and monitoring. These phases commonly involve key actions in sourcing, procurement, logistics management, quality assurance and delivery as SCM technologies and workflows aim to optimize efficiencies across the entire chain measuring efficiency, productivity and opportunity for continuous improvement.

Demand signals, past performance, supplier availability of each component to the finished delivered product all play a part in getting your 100 bottles into the hands of your loyal customers. SCM intentionally predicts, orchestrates and optimizes each stage of production, execution and delivery to ensure that every element is rightsized and in lock step with all other stages.

Now: close your eyes and imagine that instead of pickles, we were talking about content. Instead of talking about profit from selling pickles, we were talking about opportunity that is driven from a customer’s journey and their engagement with content.

What Should a Content Supply Chain Really Address?

The purpose of a content supply chain is NOT to make more content faster. It is to generate the right content for the right audience or customer in the right moment. In the earlier example of our pickle business, the end goal of an optimally managed supply chain is not to make more pickles faster. Instead, it works to get the right jar of pickles into the right customer hands to meet an immediate craving and need in the right moment. Miss that window, you risk missing that sale.

Through this same lens, if we are working to make content, there needs to be an end business goal that answers the question of WHY are we doing this to begin with. We produce content so that we can manufacture opportunity and growth thanks to engagement.

If we only focus on automating the process of content operations, we only get more of the same content, produced faster. When we add Artificial Intelligence (specifically generative AI) to the mix, we get more versions of content, produced faster. However, if we focus on how we use content to manufacture opportunity, our processes, our outcomes and the technology we leverage is set to a different purpose. Instead of churning assets quickly, our gaze turns to prediction, context and timing of content production and delivery orchestration.

This is not to say that there is not intense pressure on marketing teams to create more forms of more content. This pressure has pushed the boundaries of the content development team to deputize functions and personas well outside the formal engagement center of marketing, conscripting them into this content development and deployment team.

These informal engagement hubs have often turned to rogue, self-selected tools that may produce content or assets quickly, but fail to connect to centralized common brand assets or templates. These teams are asked to be part of the machine that is manufacturing opportunity, but they are not included in the tools or platforms that could allow for brand secure creation.

The content supply chain requires specific shared services that include common data, common asset repositories and visibility across what exists in the creative world of possible. With guidelines and guardrails set across the organization, the supply chain allows for creative centralization that is built from collaborative briefs and a collective understanding of the brand and the customer.

Visibility, accountability and analytics are supported by truly digitally connected systems and tools. The data and analytics that flow across this content supply chain should not just curate and elevate insights and recommendations for optimized actions. An AI-powered content supply chain should have the capacity to reason and take action based on known factors from brand standards, allowable use guidelines, market conditions, and even current events. Predictability and scalability across the supply chain is not thanks to the speed of automating creativity, but rather thanks to the speed of identifying outliers and predicting needs to perfectly pace production, resources and collaboration. The beauty of a supply chain strategy is in the dichotomy of it all: a content supply chain should be structured to empower flexibility.

Just like with pickles, tastes for content will change. The content supply chain will allow for change. Spicy pickles could be all the rage today but fall out of favor tomorrow as sweet pickles take over. Similarly, image personalization are table steaks in today’s engagement strategies, but just like that video could be the only game in town.

Is your organization ready to manufacture opportunity?

If the answer is yes, start by mapping the stages and phases that touch. Work backwards to identify where along that process content can and should be created, individualized and contextualized to deliver a more personalized engagement with the customer. Identify where signal, telemetry and data can be curated to fuel predictive outcomes. Then, do this exercise all over again, but bring in different entry points for the customer’s journey that extend across the organization. Sales, service, finance, commerce, in-store, and even events should be thought of as part of this process to manufacture opportunity…and in turn should be accounted for across the content supply chain.

The content supply chain will continue to evolve as a strategy just like the technology stack will evolve as technologies evolve. While there won’t be a single “content supply chain stack” there will be core tools and core platforms that will connect into a larger engagement and opportunity ecosystem. Think of solutions like Adobe GenStudio and Adobe Express with all of their generative AI and content creation power connecting into larger CRM and Service solutions like ServiceNow or Cloud platforms like AWS or Microsoft to bring all that interaction and engagement together with the customer and with all those content attributes into a trusted single truth.

The content supply chain will integrate and connect far beyond Marketing and creative teams. It will account for and deliver right-sized tools across the organization and connect everyone into this overarching supply chain that manufactures durable, profitable growth, even for a pickle manufacturer that only sells 100 jars a month.

 

Image is AI generated using Adobe Firefly. No pandas were asked to pack pickles for this image.

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9 Google Cloud customers on AI implementations, best practices

There was no shortage of customers at Google Cloud Next 2025 as the company is hitting its enterprise stride with a focus on industries, use cases and integrating AI agents.

Here’s a look at customers at Google Cloud Next their takeaways and best practices picked up along the way.

Google Cloud Next coverage:

Volkswagen

Volkswagen's Steve Lancaster, Director of Connected Car Development, Operations and Connected AI for the America region, is responsible for apps, IoT platform and AI efforts. Volkswagen has been a Google Cloud customer for about 16 months.

Lancaster said the data streaming from cars and apps is valuable feedback. The problem was Volkswagen didn't have the visibility into the content and data to improve customer experiences.

"There's a lot of feedback and direct contact with the customer through this application, and we pay a lot of attention to what they're saying," said Lancaster. The requirements for Volkswagen revolved around search across multiple data types and documents and models that can learn and answer customer questions.

"We're using Gemini to really understand customer intent and Vertex AI to really break data down into its proper form and return answers. We know the most about these vehicles and we need to make that information readily available," explained Lancaster.

Best practices:

  • Follow the playbook and Google Cloud roadmap. Lancaster said it helps to learn the basics blocking and tackling on the platform to improve data and AI core competencies.
  • Focus on business results. Lancaster said he wouldn't talk about ROI savings, but said there are fewer calls to customer service. The feedback from the app provides signals as does sentiment on social media. "Customer satisfaction is measurable and tangible, and we're watching them closely. We get all kinds of feedback from the app, from the thumbs up, thumbs down to very specific comments about how it's interacting, or what they're thinking," said Lancaster. "At the end of the day we're selling cars. If we can impact the owner experience and brand loyalty that's a big measure."
  • Know your own user stories before you engage. You know your business better than anyone else and have the data before engaging.
  • Clean up your data so it's AI ready ahead of the AI project.
  • Beware of the "laptop AI guy" who shows what was possible with a model. Lancaster said AI is an IT project that needs security, compliance and everything you need in the enterprise.

Best Buy

Ashley Daniels, Vice President of Product Management at Best Buy, said the retailer is in a broader customer care transformation and moving beyond stitching together experiences beyond the call center.

Daniels said genAI is enabling agents to lead with empathy since AI can take the notes. "We're now in the IVR and chat bot transformation," said Daniels, who said Best Buy has been transforming its customer engagement and experience for the last 18 months.

Best practices:

  • If you have contact center use cases, there are plenty of ROI measures. Daniels said the previous IVR system would route to an agent when a customer tried to cancel a membership. The problem was an inconsistent experience. Now Best buy can pull data on savings and coverage for devices and increase the save rate. "The day it went live the contain rate went form 9% to 50%," she said.
  • Continually optimize. Daniels said Best Buy continuously changes the system to leverage AI and tweak the experience.
  • Create human experiences using AI. Don't lose track of the human element.
  • Best Buy using AI agents going forward will improve customer satisfaction and drive revenue, said Daniels.

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Geotab

Neil Cawse, CEO of Geotab, has a business that manages vehicle fleets. Geotab leverages Gemini in its products and in analytics as well as Workspace.

Cawse said Geotab is focused on data residency and where it resides. "We can't tolerate data being in the wrong places," said Cawse.

Best practices:

  • Focus on adoption. Cawse said the company is following the usage data. By tracking usage, Cawse was able to discover that HR didn't use Gemini nearly as much as marketing.
  • Notch small wins. Geotab uses town halls to highlight examples of good AI usage internally.
  • Find new ways of working. Processes and workflows change with LLMs.
  • "We have the opportunity to leverage AI to take away the laborious work and enable AI agents to automate tasks," he said. "Humans will still run the show, but you'll have agents running behind the scenes doing the work."

Gamuda Berhad

John Lim Ji Xiong, Chief Digital Officer at Gamuda Berhad, said his Malaysia-based construction firm is focusing on AI via Google Cloud and "trying to insert technology for all of our property and construction business."

Xiong said Gamuda Berhad has 164 agents in production. He said:

"We're at 164 across all sorts of different areas, whether it's contract analysis, whether it's looking at the design documents, whether it's looking at tender documents, being able to speed up our time to put in proposals, being able to also then get information across the organization, whether it's Australia to Malaysia. We're seeing a 20% increase in our funnel."

"These are customers that would not have necessarily come through our sales gallery, but they are interacting with us already."

Best practices:

  • Transform your industry. Gamuda Berhad is now starting a tech services unit to branch out from construction.
  • Gamuda Berhad has just completed the second phase of its transformation by consolidating data in BigQuery. Now the plan is to leverage data to "create a crystal ball for construction," said Xiong.
  • Upskill. Xiong said his company has created an AI academy to get people from all walks of life to learn AI. "We use a full-stack syllabus," he said. "We can get people up to speed in three months." The company has graduated two classes of 50 and is expanding the class to the rest of the country.
  • Build a talent base. Xiong said his company is hiring some of those graduates.

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WPP

Stephan Pretorius, CTO WPP, said the advertising firm started out with Google Cloud focused on workflows and when genAI landed the company started using it for content and ideation.

"As the models have become more capable, the latest unlocks for us have been video and we saw an explosion of video usage inside the business," he said. "Going in we saw a new pattern of behavior."

WPP also has 2,800 agents in production for contract review, CRM automation and other use cases.

Best practices:

  • Pretorius said enterprises need to focus on adoption, change processes and the way they think. "Adoption is a huge metric. We track, time spent and tasks," he said.
  • AI can drive new ideas quickly and you pretest concepts for media campaigns as well as returns for customers. But unit economics are a challenge. WPP used to charge for creative by new sizes and markets. Now that revenue stream is gone.
  • "For most of our clients, AI is enabling them to keep their spend and get same reward or spend more to get more," he said.
  • Embrace the business changes and adapt. WPP's business model has changed dramatically.
  • Focus on ecosystems. Pretorius said it makes sense to pick vendors that work across systems and data stores. Open ecosystems matter so you don't get boxed in architecturally.

Palo Alto Networks

Palo Alto Networks' Rajesh Bhagwat, Vice President of Engineering at Palo Alto Networks, is responsible for data platform and AI. Palo Alto Networks has been a Google Cloud customer since 2020.

He said Palo Alto Networks cloud transformation aligned with the overall product strategy, which now revolves around its Cortex platform today. Bhagwat said Google Cloud was able to offer real time data analysis via BigQuery.

Best practices:

  • Focus on tangible business returns. Bhagwat said uptime and customer satisfaction. Palo Alto Networks was able to reduce its mean time to resolution for customer issues. "When a case comes in, the support personnel is using AI assist for a quick respond back. The AI assistant knows the customer context, knows all the data is using the underlying models bring out all the reasoning, all the analysis," he said.
  • Know whether you should build or buy. Bhagwat said enterprises need to know their core competencies. It was clear that Palo Alto Networks wouldn't train its own models and run massive data centers at scale.
  • Prepare for scale. Bhagwat said scale matters. Plan ahead for it. Palo Alto Networks manages 5.5 petabytes of data each day.
  • Address skill gaps via learning but balance between broad and deep knowledge of AI. Look at new hires through the lens of AI readiness.

AI21

Pankaj Dugar, Senior Vice President and GM at AI21 Labs, said the company which develops models is using Google Cloud for infrastructure.

"As a company we do two main things. We build highly optimized foundation models. And we recently launched an AI planning and orchestration system," said Dugar.

Best practices:

  • Leverage hackathons to find talent and upskill as new technologies emerge. Dugar said AI21 connects his engineers to Google Cloud experts to learn how to use new features and services.
  • Be an early adopter. By adopting Google Cloud services early, AI21 creates a feedback loop to improve products on both sides.

Citigroup

Citigroup CTO David Griffiths said the banking giant is leveraging Google Cloud as part of its multi-year transformation. "Anywhere we work with digital transformation, AI can help. We are embracing AI as a universal enabler," said Griffiths.

Griffiths outlined the strategy and best practices:

  • "We've been guided by a couple of simple principles, with taking a very deliberate approach. We build a simple, scalable, secure, multi-model platform that has centralized controls and observability, so we can keep everyone safe, and we can learn and observe across the breadth of all of our AI interactions."
  • "We think about the impact of AI in two dimensions: General, horizontal, assistive AI tools that have very wide applicability. These may only give you 1% to 3% of productivity back, but you scale that across the company, this really adds up. And you have to complement that with deeper AI verticals, specialized capabilities for the specialists within your workforce."
  • "A scale footprint allows us to maximize the impact as this technology advances. Google is at the frontier of AI development, and we want to have a mini lag between AI innovation and AI impact."

Griffiths added that Citigroup had about 1,000 use cases in 2024 at various stages. Those use cases were horizontal and could benefit the entire organization. In 2025, Citigroup is focused on scale and depth and "industrializing our AI verticals" for customer servicing, fraud detection, finance and sales and marketing.

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Citigroup’s journey

Pearson

Pearson CTO Dave Treat said the education and learning company is transforming to "use AI to help educators and students transform learning across all stages of life." And the company is betting on agentic AI.

"We've realized it's time for us to think outside the book, and we're really just at the beginning now of creating super effective, personalized learning experiences using agents," said Treat. "We're envisioning a team of agents working together on behalf of educators and students using natural language interfaces integrating all of the tools and resources that they need guided and shaped by our learning science and trusted content."

Treat noted that agentic AI will change its engineering and software development lifecycle. Pearson is using specialized agents for code, documentations, and testing scripts.

According to Treat, Agentspace will be the control plane for multiple agents including ones from Salesforce and ServiceNow. Treat's take highlights how hyperscalers may be best suited to orchestrate AI agents across systems. "Just like humans, there's going to be the right agent for the right job," said Treat.

 

 

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Canva launches Visual Suite 2.0, adds Canva Sheets, Canva Code

Canva launched its Visual Suite 2.0 in what it calls the biggest product launch since it was founded in 2012. Canva aims to make spreadsheets visual with Canva Sheets and create interactive designs with simple prompts with Canva Code.

The company announced Visual Suite 2.0 at its Canva Create event in Los Angeles. Canva's Visual Suite overhaul is designed to build on its 230 million monthly active users, cater to designers as well as attract new users.

Here's what Visual Suite 2.0 includes:

  • One user interface and design. Whether it's a document, spreadsheet or photo editing, Canva's design carries over in Visual Suite 2.0. The unified design is a bid to consolidate separate tools for design.
  • Canva Sheets is an effort to reimagine the spreadsheet. Sheets is built on Canva's Magic Studio and features Magic Insights, which scans data for patterns and takeaways. Canva also added connectors to import data from HubSpot, Statistica and Google Analytics.

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  • Magic Charts takes data and makes it interactive with visuals ranging from visualizations to infographics.
  • Magic Studio at Scale has bulk content creation with personalization.
  • Canva AI generates and edits designs, text and images.
  • Canva Code creates designs from natural language prompts and applies to presentations, landing pages, classroom resources and interactive designs.
  • Photo editing is also available as a standalone or integrated tool.

Melanie Perkins, CEO of Canva, said the goal with Visual Studio 2.0 was to meld creative and productivity workflows with one design.

Canva continues to gain traction with a model that offers free services and upsells to prosumers as well as enterprises. Canva has more than $3 billion in annual revenue, up 30%. Canva counts T-Mobile, Salesforce, FedEx and DocuSign as customers.

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ShortList Spotlight: Kodem Security

There's a seismic shift happening in how we develop and secure #software. 🔐 Developers are no longer just writing code - they're navigating a complex ecosystem of #AI-generated #applications. 

Modern apps are interconnected with multiple systems and rely on numerous open-source packages. In these dynamic, unpredictable environments, attackers hunt for interaction vulnerabilities - a single weak link that can compromise an entire system. 🔎 

Enter Kodem Security 🔒 Kodem was named to the Constellation ShortList as a solution leader in Application Security Testing. Constellation analyst Chirag Mehta explains Kodem's approach to...

🔍 Scan code statically and dynamically
🔬 Track runtime vulnerabilities
🌐 Understand complex application interactions

Watch this ShortList Spotlight to learn more about Kodem 👇 and start reimaging application #security in the AI era. 

View the full Constellation ShortList here: https://lnkd.in/gh6wqXqv

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