From boardrooms to shop floors, companies are moving quickly to embed AI into their operations. The goals are clear: drive efficiencies, reduce costs, and deliver smarter, faster, more personal customer experiences.

This makes a lot of sense given that today 89% of businesses are expected to compete primarily on CX. However, the results aren’t always matching the hype.

A recent Gartner study found that while enterprise AI adoption is rising, real impact is often elusive. The reason? Many businesses are still operating with disconnected systems and disjointed data. Without a strong foundation, AI can’t deliver what it promises.

Siloed systems aren’t just a technology problem—they’re a business barrier.

The CX Disconnect: When Fragmentation Undermines Intelligence

Too many organizations still rely on a patchwork of tools for customer experience, supply chain, finance, and HR. While these point solutions solve individual challenges, they create friction and disconnect across the business. In an AI-powered world, friction is the enemy.

AI thrives on complete, clean, and contextualized data to function effectively. If your marketing, sales, service, and fulfillment teams cannot see the same data in real time, or trust that it’s accurate, your AI strategy will not be set up to succeed.

With the best intentions to embrace AI in an effort to achieve incredible efficiency, instead, customers will still lose valuable time on manual integration, inconsistent customer experiences, and AI outputs that are only as good as the (fragmented) data feeding them. The delightful experience aspirations turn into trust lost and frustration all around.

Modular Innovation, Meet Enterprise Intelligence 

SAP has reimagined enterprise management with SAP Business Suite, representing a fundamental shift from traditional ERP systems to a modular, composable architecture that integrates AI, data, and applications into a unified platform.  

Grounded in harmonized, semantically rich data, this architecture allows businesses to make sense of data that has traditionally been scattered across systems and trapped in silos, so AI has the comprehensive data it needs to quickly generate meaningful insights.

SAP Business Data Cloud (SAP BDC) with native integration of SAP Databricks, serves as a data backbone for business AI. It seamlessly connects all SAP data and third-party data and provides integrated governance to enable real-time AI-driven decision making.  

Companies do not lose precious time locating and preparing data for AI. AI systems work on trusted, contextualized data, not just generic data. This produces accurate, reliable, and actionable AI recommendations that enable organizations to scale AI innovation rapidly across business domains. 

SAP BDC is the foundation for Joule, SAP’s AI copilot that acts as an intelligent orchestrator across the entire business suite. SAP BDC ensures that Joule has structured business context for natural language processing and that its outputs are accurate so that Joule can provide always-on assistance to break down silos between business operations. 

For example, when a customer service or sales representative handles a complex order issue, Joule can: 

• Check real-time supply chain constraints

• Respond to RFPs faster
• Personalize the response by pulling in relevant customer history from CRM systems
• Speed response with automated case routing and research

The results are faster resolutions, happier customers, empowered employees, and incredible business outcomes with less effort and overhead.

CX + AI + ERP = Real Results

Integrating CX AI with core ERP systems enables end-to-end process optimization that was previously impossible with fragmented systems. When CX systems connect natively to back-office systems, organizations gain: 

• Real-time personalization powered by operational data
• Intelligent workflows that prioritize high-value customers
• Predictive insights that help teams act before issues arise

The numbers speak for themselves. According to an Enterprise Strategy Group report, customers using this approach reported these benefits:

• Up to 60% reduction in the number of issues service and support teams deal with due to fewer manual errors, automated self-service support functions, automated self-service, and AI chatbots
• 25% to 50% improvement in time to resolution for issues that did require service or support resources
• 25% to 70% improvement in productivity of digital marketing and customer operations teams
• 50% to 90% improvements in sales team productivity by offloading smaller transactional sales, faster quote generation, and streamlined order management
• 20% to 40% increase in productivity of business operations due to less time spent on invoices, payments, shipments, and returns and more informed decision-making

This is not just incremental change; it’s enterprise transformation, driven by customer needs and powered by AI.

The Future of Intelligent Enterprise Operations 

Embedded CX AI within a composable business suite represents a bright future that takes the possibility of AI and makes it a reality. 

• Businesses can seamlessly orchestrate intelligence across all functions, delivering experiences that feel effortless to customers while optimizing operations behind the scenes. 
• Artificial intelligence won’t just automate individual tasks, but also orchestrate entire business ecosystems to deliver superior outcomes.  
• Maintaining enterprise-grade reliability and enabling modular innovation will allow organizations to adapt to changing market conditions while creating competitive advantages. 

With the rise of AI, businesses face a pivotal moment in time. Taking advantage of all that technology has to offer demands more than point solutions and departmental optimizations; it requires unified platforms, complete clean underlying data, and a clear unified strategy.

Jessica Keehn is chief marketing officer of SAP Customer Experience.

Before his portfolio management days, Denny Fish worked as a sales manager at Oracle. He saw the incredible demand for its software products as the dot-com boom flourished, an experience that would later inform his mindset as an investor: What was the next revolutionary idea he could get ahead of?

“I watched the internet boom, I had a front row seat because I was at Oracle and we were in the eye of the storm,” Fish said. “So it shaped my investment philosophy of, ‘Wow, always be looking for that big idea.'”

He continued: “Because the big idea is gonna express itself in a way that nobody can appreciate over multiple years and when you get behind that big idea, don’t let anybody shake you out of it because that’s what’s called a power law in technology investing.”

Two decades later, Fish was perfectly positioned for the AI boom. As a co-manager of the Janus Henderson Global Technology and Innovation Fund (JAGTX), his top holdings are a who’s who in the AI ecosystem: Nvidia, Microsoft, Taiwan Semiconductor, and Broadcom. Those four names alone, all of which he’s held for more than a year and a half, make up 42% of JAGTX.

The impressive lineup has led to a banner few years for Fish. Since the October 2022 lows, his fund is up 136%, crushing the S&P 500’s 81% surge.

Today, Fish still thinks AI is the big idea to get behind. But when asked which stocks he’s most bullish on right now, three out of the four were companies outside his top six holdings in the 25-stock fund.

4 stocks Fish likes right now

The first firm Fish listed — and the one that is among his largest holdings — is Taiwan Semiconductor, as chip demand remains uber-strong. It’s the fund’s third-largest holding at 9.49%.

“If you’re a Broadcom or if you’re Nvidia, there’s only one place you want to go to get your chips manufactured, and that’s TSMC given their process, know-how, and the lead that they’ve created,” he said.

Next, he said Cadence (CDNS), an electronic design automation firm, is well-positioned for continued AI hardware demand. The stock is the fund’s eighth-biggest holding at 2.47%.

“It’s a global duopoly,” he said of Cadence and its competitor, Synopsis. “They have dominant market positions, incredible returns on capital, and there are businesses that you can’t move forward with chip design without one of those two companies.”

Third, Fish is bullish on KLA (KLAC), which produces process control systems for semiconductor chips. The firm “has a very dominant position globally, in that swim lane for, for semiconductor capital equipment,” Fish said.

At 1.88%, it’s JAGTX’s thirteenth-largest holding.

Finally, Fish mentioned Mercado Libre (MELI), a Latin-American e-commerce platform with a fintech business that offers digital wallets, lending, payment solutions, and money transfers. Fish said he’s impressed with the company’s use of AI.

“They’re doing really unique things with AI through their entire portfolio to improve the customer experience and also improve their underwriting and their fintech business,” he said.

Mercado Libre is the fund’s seventh-largest holding at a 2.64% weighting.

A version of this story appeared in CNN Business’ Nightcap newsletter. To get it in your inbox, sign up for free here.

New York
 — 

Oracle, a large but generally sleepy cloud-computing company, just had an absolutely bonkers day on Wall Street.

The stock (ORCL) shot up more than 40% Wednesday morning, its largest single-day jump ever. It was such big leap that it minted Oracle co-founder Larry Ellison $100 billion in less than hour, making him the world’s richest person and bumping Elon Musk to second place.

The catalyst wasn’t a flashy product rollout or a surprise earnings beat — in fact, Oracle’s quarterly revenue and profit came in below Wall Street’s expectations Tuesday evening.

Instead, the fire came from Oracle’s outlook for the next few years, which, if it pans out, would cement the company as a power player in artificial intelligence. That’s a big “if,” though — especially given that the bulk of Oracle’s rosy outlook hinges on revenue from one major customer, the unprofitable OpenAI, according to the Wall Street Journal.

Oracle’s outlook is “so exuberant that if we’d gotten this sort of prediction from a less established company it might have been shrugged off as either a lie or a misplaced digit,” Steve Sosnick, chief strategist at Interactive Brokers, told me.

Here are the key things powering Oracle’s stock at a clip it hasn’t experienced since the late-90s dot-com-bubble era, when it rose nearly 600% in the span of a year before falling back to earth by 2022:

Oracle, which sells database software, has somewhat quietly ingratiated itself to investors in the AI gold rush this year by securing deals with AI companies hungry for computing capacity. (If semiconductor giant Nvidia (NVDA) is the “picks and shovels” play of the current frenzy, think of Oracle as the Levi Strauss play — it’s not mining the gold, just providing durable trousers.) And now it’s making its debut as a force to be reckoned with against rival cloud-storage providers like Google, Amazon and Microsoft.

If Oracle’s head-spinning projections seem too good to be true, well, that’s all part of the fun-house mirror effect of the generative AI bubble (yes, I said “bubble”). Because for any of Oracle’s future projections to make sense, its AI customers, including OpenAI, have to make, like, a lot of money — something the ChatGPT maker has shown no clear path to doing anytime soon. (The Information reported last week that OpenAI’s projected cash burn this year through 2029 will hit $115 billion — about $80 billion higher than the company previously expected.)

Like other big tech names, Oracle is betting much of its future on the promise that demand for computing capacity will keep going up as generative AI ushers in some kind of as-yet-undefined revolution. So tech companies are spending hundreds of billions of dollars to build out the data centers — giant, energy-sucking buildings full of computer servers — to ensure the US has the technical infrastructure to deliver all of the AI magic.

That gamble on infrastructure is so massive it actually eclipsed consumer spending this year as the main driver of GDP growth, according to Renaissance Macro Research.

“This data center buildout continues to be a major support to the US economy… so we of course hope that Larry Ellison is right and that this massive buildout is sustainable,” Peter Boockvar, chief investment officer of One Point BFG Wealth Partners, said in a note Wednesday.

But Boockvar also sounded a note of caution: “While Oracle just knocked the cover off the ball, when I see one day market cap increases of such epic proportions, I can’t not think of what I witnessed in 1999.”

(Ahem, 1999 being the start of the dot-com crash.)

Oracle’s capital expenditures are “truly extraordinary,” at $35 billion for this fiscal year, which is about 52% of revenue, Boockvar notes. In 2024, it was 13% of the company’s revenue. “We’ve never seen such capital intensity from these previously large-free-cash-flow-generating businesses.”

In other words, Oracle is a huge company, and it’s never spent money like this ever before.

The risk here, of course, is that Oracle’s big customer, OpenAI, doesn’t deliver.

Generative AI, the engine of ChatGPT, is one of those rare technologies that manages to get less marketable over time. The more many regular people encounter AI in their lives, the more they come to associate it with “slop” on their Facebook feeds. Chatbots cannot reliably respond to human beings’ queries, and they have a pesky tendency of dragging said humans into delusional, at times deadly, mental spirals.

It isn’t completely useless, to be sure, but AI’s proponents have had an extremely difficult time building an application that’s lived up to their own hype (nor, certainly, has any of it lived up to the lofty valuations propping up American tech companies).

Without a game-changing tech update that either drastically lowers its costs or dramatically boosts its profits, OpenAI may be toast. And that presents a systemic risk to not just Oracle, in particular, but to the tech sector more broadly.

If Oracle can stick the landing, Sosnick said, “then by all means, this rally is well-deserved.”

“Yet you are correct in pointing out the risks inherent in the market’s complete revaluation of Oracle… Not only are Oracle stockholders crucially dependent upon the company meeting its guidance, but the broader market is, too.”