Tim Banting doesn’t mince words. “Given that we’ve just had Halloween, I’m introducing the term: Frankenstack,” says the Head of Research at Techtelligence. The definition?

“A horrible cobbled together layering of bots and automation and analytics.”

It’s a vivid metaphor for a very real enterprise challenge. In their race to modernise customer experience, many organisations have piled on AI tools, each solving isolated problems but collectively creating confusion. He explains:

“They’ve hit this wall where adding tech adds cost and complexity and it doesn’t provide any degree of clarity.”

Instead of scaling value, enterprises are scaling frustration.

From AI overload to orchestration clarity: Making CX systems sing

The pendulum, Banting argues, is now swinging back. “What we’re looking at now is this resurgence of journey orchestration,” he says. “It offers a way to make existing systems talk to each other and automate handoffs between these Frankenstack systems.”

He explains that AI excels at optimizing moments within the customer journey, for example, agent assist tools or chatbots handling simple transactions. However orchestration optimizes the full journey.

Banting compares it to a conductor leading an orchestra: “You don’t have the brass section doing their own thing and percussion doing their own thing. It really does require something at the top to help guide it, coordinate it, schedule it and orchestrate that journey.”

Ultimately, the goal should be not more machinery but a smoother flow.

The buying shift: From AI expansion to workflow simplification

Techtelligence’s latest data backs up this trend. “Buyers aren’t hunting for new AI platforms,” Banting confirms. “They’re researching workflow orchestration, data unification, and process simplification.”

This is the latest chapter in 2025’s quietly growing trend – a lean towards ‘cost to serve’ as the key metric for success. Especially as enterprises are under pressure to do more but with a fewer headcount.

When “every customer interaction involves three or four different systems and multiple handoffs, your cost to serve really skyrockets”, Banting says. Automating this process is where orchestration shines, enabling enterprises to increase productivity.

Less tech, more flow

As enterprises consolidate, one message rings clear: the AI arms race is over; orchestration wins the war on complexity.

“There’s no one platform to rule them all,” Banting concludes.

“You really need to do your due diligence and talk about workflow integration with vendors. That will become more important to get the best productivity, both from individuals and also from teams.”

Orchestration is the quiet revolution bringing order to the AI chaos – and the smartest CIOs and CX leaders are already tuning in.

Keep up to date with the latest tech buyer trends

Find Tim’s full analysis on Techtelligence.

If you’re an enterprise technology buyer or involved in procurement decisions for your business, follow Techtelligence on LinkedIn for weekly insights, analysis, and expert advice to help you make smarter technology choices.

You can also join its growing LinkedIn Community Group to discuss trends, share experiences, and connect with like-minded business professionals driving digital transformation in their industries.

X (formerly Twitter), ChatGPT, Claude, Perplexity, Spotify and payment giant Square were among those caught up in the fallout.

The trouble began just before 11:48 GMT, when Cloudflare posted that it was dealing with an “internal service degradation” causing intermittent outages across its service network. Users saw error pages, stalled logins, broken APIs, and sites claiming connections were blocked. There were a few conflicting signals about the restoration progress, as at one stage the company reported that services were beginning to recover, but then around 15 minutes later reverted to “continuing to investigate this issue.”

By 13:04 GMT, Cloudflare admitted that one of its fixes involved disabling WARP access in London entirely, temporarily cutting off users from its WARP performance-boosting and VPN service that helps secure and accelerate internet connections:

“During our attempts to remediate, we have disabled WARP access in London. Users in London trying to access the Internet via WARP will see a failure to connect.”

Cloudflare announced a fix five minutes later, but continued to receive “reports of intermittent errors” until close to 17:00 GMT.

Untimely Outage Exposes Weak Spots in Online Payments

While the broken pages and error messages got the immediate attention, the real pain from such outages often comes from the disruption to payment flows. Failed transactions, repeated payment attempts, and unclear confirmations create a backlog of problems that merchants have to untangle later.

As Monica Eaton, Founder and CEO of Chargebacks911 and Fi911, said, “When major websites hiccup, users notice. When payment processors flicker, the ripple effects get messier—and much less visible.”

When customers are unable to complete payments, or worse, the system wobbles cause duplicate payments, the chaos continues beyond the initial outage.

“What actually happens during an outage like this is messy. Customers retry purchases, cards get hit twice, confirmation pages stall, and suddenly you have a wave of confusion that turns into disputes. By the time the dust settles, merchants are left cleaning up charges they never intended to send in the first place.”

And the timing of this particular outage, during the shopping days leading up to Black Friday, caused further headaches, as Charlie Jackson, Executive Director of Gumpo Digital Marketing, pointed out:

“This is not just a typical server blip, this is a multi-million pound algorithm disruption hitting the digital marketing world at the worst possible time. With major e-commerce brands down and around 80% of our clients relying on Cloudflare, we had no choice but to immediately hit the pause button on high-spending PPC and paid social campaigns.

That will not only affect revenue on the day, but will have a knock-on effect on retailers’ performance over the Black Friday period, Jackson said, because advertising platforms like Google and Meta use machine learning. “When you interrupt high-performing campaigns, you essentially disrupt the algorithms’ constant flow of data needed to optimize budgets and target audiences effectively.”

The hours-long outage could cost the retail sector millions in disrupted campaigns and lost momentum during the biggest shopping event of the year.

“We’re in the most critical 10-day scaling window before Black Friday and this outage has once again flagged the impact CDN outages can have and that though they bring benefits on the whole, they do leave sites vulnerable and at the mercy of Cloudflare to resolve these issues,” Jackson said.

Repeated Cloud Outages Are Exposing Systemic Weaknesses

Cloudflare’s stumble, coming shortly after massive outages in the past month at AWS and Microsoft Azure that caused their own waves of disruption, has given more fuel to warnings over the dependence on a small number of global infrastructure giants. As Eaton noted:

“Cloudflare going dark today should snap every merchant back to reality. We keep building bigger online businesses, yet so much of that growth depends on a few invisible services holding everything together. When one of them goes down, even for a moment, the internet feels like a house with loose wiring. Lights flicker everywhere. Payments included.”

Mike Hoy, CTO at Pulsant, has warned that the concentration of workloads in the hands of so few providers creates systemic risk. His concern is twofold: the technological fragility and the lack of practical recovery planning among businesses. “Encouragingly, many organizations are already moving away from dependence on a single public cloud provider. Recent research from Pulsant reveals that 87% of businesses plan to partially or fully repatriate workloads over the next two years—up from 43% in 2021, according to Barclays.”

But that shift isn’t simple, as regulatory constraints, data transfer costs and platform lock-in all slow the transition. These outages expose the vulnerabilities of the current model and why a more competitive and distributed cloud ecosystem is needed, Hoy said.

“True resilience requires workloads to span colocation, private infrastructure, and public cloud. Colocation sites provide critical support when primary facilities fail. They offer regional diversity, robust physical security, and the connectivity needed to bridge private systems with cloud platforms.”

But this only works if recovery strategies stay consistent and coordinated. Otherwise, the slowest backup system becomes the bottleneck, Hoy added. As enterprises plan for the year ahead and beyond, they need to build recovery into their digital architecture.

Eaton stressed that businesses shouldn’t view infrastructure faults as rare surprises that leave them scrambling. Instead they should account for them as operational realities that need structure and preparation.

“Treat outages like this as part of normal operations instead of strange one-offs.

Practical steps can prevent minor glitches from turning into major financial cleanups: “Track failed and duplicate transactions. Talk to customers before they start guessing what went wrong. Make a quick log of what happened today so you are not trying to piece it together weeks from now when chargebacks start landing.”

Financial services have been especially rattled by the repeated outages. After the recent AWS outage disrupted several major UK banks, the Financial Conduct Authority warned that the UK needs to “strengthen” its oversight of foreign tech providers.

“The FCA’s latest warning underlines how heavily the UK’s financial system now relies on a small number of foreign companies to deliver the core digital services it depends on,” Vivek Dodd, CEO at Skillcast, said.

“Such disruptions expose not just technical faults but broader challenges around operational resilience and business continuity in a hyperconnected economy.”

While many financial institutions have made progress in digital transformation, their contingency strategies often still assume the reliability of third-party partners, Dodd noted. But “even the most sophisticated global tech firms are not immune to outages or cyber-attacks, and the consequences for customers and markets can be significant.”

Enterprise continuity and recovery plans should map critical dependencies and identify single points of failure, Dodd said. They should include layered contingency measures such as multi-cloud or hybrid hosting strategies, and proactive communication.

“Ultimately, resilience isn’t just about protecting systems; it’s about preserving customer trust and safeguarding organizational reputation in an increasingly digital world,” Dodd said.

Indeed, the underlying concern is bigger than a single provider’s bad day. Between AWS, Azure, and now Cloudflare, outages are coming more often, and the consequences are hitting more critical services.

The goal is to stay grounded and tighten the parts of the process that businesses can actually influence, Eaton said.

“None of this is about panic. It is about owning the risks you can control. Cloudflare had an outage today. Another provider will have one tomorrow. What matters is whether businesses learn from these moments or keep hoping luck will cover the gaps.”

Businesses need to wake up to the fact that the internet’s backbone rests on fewer pillars than most customers realize, and those pillars are wobbling more often.

In its quarterly report on Wednesday, the technology company revealed several high-value investments in its AI products. 

In the earnings call, Cisco emphasized that this rapid growth in AI product adoption indicates a rising demand for secure networking. 

Customer-Centric Strategy 

Over the past year, Cisco’s quarterly results have demonstrated high levels of growth after several previous declines, and it is now reaping the benefits of its increased customer spending and investment. 

This has included various AI products and suites, as well as investments in data centers to support the demands for AI-driven workloads and cloud networking. 

However, the attention has turned towards its customers and their willingness to adopt these products into their workflows. 

Despite this growth in demand, a Cisco study revealed that only a third of companies are certain that their IT infrastructure can safely integrate their AI projects, which Cisco views as favorable for them. 

With its extensive networking portfolio, the company believes it is on track to deliver the critical infrastructure to its customer enterprises, enabling them to adapt to the AI era. 

Modernizing Customer Experience 

In response to the study, Cisco has acknowledged that many companies are still far off from where they’ve been expected to be with AI. 

Charles Robbins, CEO and Chairman at Cisco, recognized the readiness gap between planning and execution when it came to adopting AI. 

He said:

“We know many customers still have a lot of work to do to ensure they have the modern, scalable, secure networking infrastructure to support their AI goals.” 

Cisco has already begun its move toward a modernized customer experience through various upgrades and expansions, allowing for simpler large-scale AI deployments. 

This has included its global network and infrastructure upgrades, allowing Cisco to enhance its enterprise switching, routing, and Wi-Fi to conduct large-scale AI and data-intensive workloads with fast, scalable, and secure performance. 

From this, Cisco expects its enterprise customers to switch from legacy networking equipment to its newer systems, collectively spending billions as part of its multiyear, multibillion-dollar refresh opportunity. 

With global data expansion, Cisco has established numerous regional data centers worldwide, as well as a European customer-based sovereign critical infrastructure portfolio, focusing on a global scale-up with region-focused deployments. 

By supplying software and cloud-native transformation, customer enterprises can also receive automated network surveillance and deliver secure, scalable customer experiences. 

In addition, Cisco offers end-to-end security integrated into the network, supporting modernized infrastructure for reliable and capable traffic pattern management. 

Workloads with Agentic AI 

Cisco’s earnings call reported a surge in agentic AI activity, with the number of queries through agentic AI measuring at 25x higher in network traffic than chatbots. 

And demand for AI has increased with it, with Cisco expecting AI infrastructure to generate $3BN in revenue for fiscal year 2026. 

A contributing factor is the AI workloads needing the necessary models and infrastructure to process locally. To support this, Cisco announced the release of its Unified Edge last week, as part of its strategy to process AI at a speedier and secure level. 

This platform offers integration for compute, networking, and storage into one system, enabling enterprises to receive real-time predictions and decisions for secure AI management. 

Another recent release is the Cisco Data Fabric architecture, which allows for the unification and management of various machine data sources, enabling companies to create more innovative AI models, adding to Cisco’s value when it comes to technology investments. 

Cisco Webex Winter 2025

Cisco has also published its Webex Winter 2025 press release, detailing its recent updates in CX technologies. 

Some key results from the season include: AI translation capabilities now expanding to 120 languages for meeting summaries; its regional cloud infrastructure locations such as the UK, Saudi Arabia, South Africa, and the UAE; a 3D workspace designer for visual blueprints; and AI Assistant for Calling for live and post-meeting summaries. 

These help to enable higher productivity levels, improve global coverage, and drive flexible working systems, with Webex allowing customers to use meeting rooms, calls, and contact center through one platform. 

However, not all these features are available for deployment as of yet. 

In conversation with CX Today, Tim Banting, Head of Research at Techtelligence, discussed Cisco’s decision to strengthen its overall CX stack across AI, global scale, and device flexibility. 

He said, “The move aligns with current Techtelligence buying-intent data showing a 19% rise in enterprise research around UC productivity and automation, involving more than 29,000 companies actively investigating process and workflow automation in communications suites. 

“However, Cisco faces an execution challenge. Several key AI and automation capabilities remain in the “coming soon” category, creating a perception gap in a market that rewards immediacy and credibility. 

“Techtelligence data shows that buyers are rewarding vendors delivering deployable automation and measurable risk controls now – not future roadmap promises. 

He added: “For CX buyers, the practical value lies in features that are globally available and compliance-ready today. The platform consolidation trend is undeniable.  

“Cisco’s success will hinge on whether it can deliver AI responsibly, at scale, and ahead of rivals who are already reshaping perception around “secure AI collaboration.” 

Cisco Key Earnings Results

After enterprise customers’ strong demand for its AI products, Cisco has risen above estimates for the quarter. 

• Cisco’s revenue is up to $14.9BN, increasing 8% year-over-year  
• Its product orders are up 13% year-over-year, with growth across all markets and geographies 
• AI infrastructures currently stand at $1.3BN 
• Service revenue increased by approximately 2% 
• Product revenue increased by approximately 10%

Christian Draeger, who runs passenger experience there, talks about it in a way that’s surprisingly down-to-earth. “We’re not just starting at the airport door,” he says. “We’re already looking at customers, how they can get prepared for their travel, even days ahead of the actual travel plans.”

That’s a different way of thinking about travel, one where the airport is part of the journey, not a pause in it. Draeger’s rule is simple: “Put the passenger in the center.”

That idea is becoming more important. Around two-thirds of travelers now use AI tools to plan their trips, and most say they want services that adjust to them, not the other way around. Berlin’s answer is to mix technology with empathy, using automation to remove hassle, not humanity, and turn the everyday airport routine into something that actually works for people.

Understanding & Designing for the Modern Traveler

Christian Draeger has spent a lifetime around airports. More than thirty years in aviation have given him a deep sense of how people move, wait, and connect. During his time with Star Alliance, he helped shape what millions of passengers now recognize as the modern travel experience. When he joined Berlin Brandenburg Airport, he came in ready to rethink that experience from the ground up.

Berlin handles around 25 million passengers a year, so it’s big enough to be busy, but small enough to still care. “We also operate our premium services: two business-class lounges and an ultra-premium lounge where you get à la carte dining and a chauffeur service to the aircraft,” Draeger said.

That same care for detail extends to the parts of the journey most people barely notice. The airport also took control of its own security operations, because, as Draeger puts it, “We felt that the mandate of the federal police didn’t provide enough attention towards the passenger experience.”

Now there are 32 security lanes, 24 fitted with advanced CT scanners, so passengers can keep laptops in their bags and carry small amounts of liquid without delay. “It’s about having a consistent experience across the whole area of the airport,” he says.

Every choice is made with the passenger in mind. “It starts really by knowing our customers,” Draeger says. “If we have a family that’s traveling once a year on holiday, their prerogatives are different from a business-class customer focused on getting through as efficiently as possible.”

That balance, efficiency for some, discovery for others, is at the heart of personalization in travel, and it’s essential. A recent study found that 93 percent of travelers now expect some form of tailored service. Berlin’s approach proves those numbers translate into real-world design decisions: better security flow, less queuing, and even duty-free areas reimagined as “specialized marketplaces.”

Dual-Terminal Strategy: Two Philosophies, One Vision

A walk through Berlin Brandenburg Airport reveals something a bit different. Its two terminals don’t just separate airlines; they reflect two completely distinct types of travelers. One is designed for comfort, the other for speed. Together, they show how personalization in travel can be built into the physical space, not only into digital systems.

“The level of automation that you will find with low-cost carriers is more in focus than with a legacy carrier,” says Draeger. Terminal 2 is the efficient, minimalist one: smaller, sharper, and geared toward travelers who value simplicity and price over perks. “Terminal 2 is geared to simplicity and generating additional revenues through add-on services,” he explains.

Think self-service kiosks, intuitive wayfinding, and a layout that helps people move quickly from curb to gate. “The utilization of busses is less, you have more walk boardings,” he adds.

Terminal 1, meanwhile, is a different rhythm altogether. “It’s about efficiency and comfort, both guided by digital tools.” Business and frequent flyers pass through airport automation that’s designed to make the process seamless. Over a hundred self-service kiosks are spread across the terminal, complemented by digital signage and premium lounges.

It’s the physical version of a digital truth: no two passengers want the same thing. Some want to breeze through with a coffee and a boarding pass on their phone. Others want time, space, and a glass of something cold before they fly. Both deserve an experience that feels intentional.

That’s what Berlin is building, a new kind of airport customer experience where infrastructure itself becomes a form of personalization. Different terminals, different tools, same philosophy: know who’s traveling, and design accordingly.

AI and Automation Enhancing Personalization in Travel

Like most airports, Berlin once relied on a traditional call center. It worked, but just barely. “We were looking at our call center and we weren’t completely happy,” says Draeger. “It was limited, inconsistent, and expensive.”

That frustration turned into an opportunity. Berlin decided to replace its call center entirely with a generative AI-powered system. The result was “Berry”, Berlin’s always-on virtual assistant.

“Customers can call the AI hotline and have a conversation just like we’re having right now,” Draeger says. It took just six weeks to build and launch, and within a few months, the results were striking: satisfaction above 85 percent, costs down 65 percent, and service available 24/7.

The human element didn’t vanish; it just found a new home. Instead of waiting in phone queues, travelers get answers right away. Lost something? Need flight details? Berry, the airport’s AI agent, takes care of it and loops in a person if the question needs a human touch. It’s simple to use too: one phone number on Berlin Airport’s website connects straight to Berry.

Building the AI Layer with Berry

Behind the scenes, Berry learns fast. “After six to eight weeks we reached an acceptable level… then you could see week-to-week improvements as GenAI learned,” Draeger explains. His team fed the system with real passenger questions and prioritized the most urgent topics first, like the classic “I left my laptop on the aircraft.” “We prioritized major customer concerns to ensure correct routing from day one,” he says.

Now the airport is preparing for the next step, chat. “We want to also offer the ability to get in touch with our AI agent through chat functionality,” says Draeger. QR codes will soon appear throughout the terminals, linking passengers directly to Berry via chat, integrated into the website and app. “If you’re standing in the arrivals hall, we’ll know based on the QR code where you are, and tailor the information accordingly.”

The idea is to build truly contextual assistance: a passenger in departures might ask about gate directions or restaurants, while someone at baggage reclaim could get help locating transport or lost luggage. “Customers can switch between voice and chat depending on environment or age. My children would prefer to talk; someone in a crowded terminal might prefer to chat,” Draeger says.

Operational AI and the Quest for Seamlessness

A lot of what makes Berlin Brandenburg Airport work isn’t something you can see. It happens on the tarmac between the terminal and the runway, where planes turn around for their next flight, and timing is everything.

“We also have others more on the ramp side,” says Draeger, referring to a system the airport now uses to track ground operations in real time. Cameras watch every stage of the turnaround, feeding data to an AI that predicts how long the process will take and where it might go wrong. “They can predict turnaround durations and steer additional resources if required,” he explains. “If a baggage belt is missing upon arrival, they can autonomously act on that and resolve bottlenecks.”

This is the kind of work that truly shapes the airport customer experience. When flights leave as scheduled, lines move faster, and connections fall into place without drama. Most travelers never think about the coordination behind it all. Yet every new piece of technology adds a layer that must fit perfectly with the rest.

But every new layer of technology brings its own challenge. “We always want to have this seamless experience for our customers,” Draeger says. “As we introduce more technology, we’ll have the challenge of combining it with legacy systems.”

Airports, after all, are built to last, and that means old baggage systems, decades-old software, and miles of wiring that can’t just be swapped overnight. “Traffic is increasing significantly, and we have limited infrastructure,” he adds. “We need simpler processes and better technology to absorb growth.”

Behind the polished front end of any airport automation project lies a balancing act: new tools talking to old systems, innovation working around concrete and cables.

The Future for Personalization In Travel: Digital Handholding

When asked what he thinks the future of travel looks like, Christian Draeger doesn’t mention drones or driverless terminals. He talks about something far simpler: help that is steady, thoughtful, and personal. “We always like to call it digital handholding,” he says. “A digital entity that’s completely informed, taking the customer by the hand and guiding them through the journey.”

Many agree that this is exactly where AI in the travel industry is heading. Gartner predicts that more than 80% of all customer interactions will be AI-assisted by 2029. The difference now is how personal that assistance can become.

“In the future, we see customers having their own personalized digital agents,” Draeger says, “on mobile, VR glasses, or other interfaces.” Those agents will be able to do a lot. “They’ll be able to rebook flights, change hotels, handle issues,” he explains. “We’ll need to provide them with the knowledge base and interconnectivity so they can act.”

He describes a world where these personal assistants talk to each other. “We’ll see a marketplace developing for agent-to-agent interaction,” he says, a network where your digital travel companion can speak directly to an airline, a hotel, or even the airport itself to smooth out the details before you notice them.

Some of that is already visible in small ways. Berlin is already imagining using augmented reality to help people find their way through the terminal. “If you come to Berlin Airport, sometimes you’ll find too many information boards,” Draeger admits. “Imagine augmented reality guiding you through the airport.”

It’s easy to see where this leads: toward an airport customer experience that blends technology with intuition. The idea isn’t to overwhelm passengers with data, but to take away the stress of travel entirely.

Personalization in Travel and Airports as Experience Ecosystems

Christian Draeger talks about air travel the way some people talk about music, not as noise and movement, but as rhythm. Airports, he says, are meant to keep that rhythm steady. When they do, everything else feels effortless.

“It’s all about making travel easier,” he says. “Like when you take a train, you just arrive and go, that’s the overarching ambition.”

Mostly, Berlin Brandenburg Airport is just pushing for a calmer travel experience. From the moment a traveler checks in to the moment they leave the gate, the goal is to take away the small frictions that make airports stressful. Berry, the AI voice agent, is part of that. So are the self-service kiosks, the CT-scan security lanes, and the quiet bits of software that keep aircraft turning on time.

“It’s not about one technology: Gen AI, robotics, biometrics, or AR,” Draeger says. “It’s about combining them to make travel much simpler.”

That line sums up Berlin’s whole approach to personalization in travel. It isn’t about showing off what technology can do; it’s about how little the traveler has to notice it.

That’s the real future of airport customer experience: an ecosystem that looks complicated underneath but feels beautifully ordinary on the surface, the kind of simplicity only achieved when someone’s been obsessing over every detail on your behalf.

This new partnership will have both companies co-developing AI-focused strategies to market to global customers. 

This partnership will also allow both to expand AI productivity on their respective platforms. 

ServiceNow and NTT DATA have begun their joint plans to market AI-driven solutions, including developing and selling these products to transform how AI is used in the workplace. 

These are set to include various enterprises, commercial companies, and mid-market segments. 

This new strategy emphasizes the companies’ previous partnerships, focusing on their commitments to advise other enterprises to adopt and execute AI into their businesses. 

ServiceNow also intends to use the expanded partnership to place NTT DATA as a delivery partner in its services to guide customers in safely deploying AI-powered automations and enhance operational efficiency. 

Amit Zavery, President, COO, and CPO at ServiceNow, highlighted how this new partnership development will improve AI across businesses, stating:

“ServiceNow and NTT DATA are expanding access to AI-powered automation across any industry and any geography to achieve measurable business impact for organizations at every stage of the AI journey, 

“Together, we’re transforming how the world’s leading enterprises operate, making work simpler, smarter, and more resilient with the ServiceNow AI Platform.”

NTT DATA will be using the partnership to escalate the ServiceNow AI platform to its business to improve its levels of productivity, efficiency, and make improvements to its customer experience across the enterprise, by adopting its AI agents and Global Business Services. 

Abhijit Dubey, President, CEO, and Chief AI Officer at NTT DATA, emphasizes how the partnership can benefit both NTT DATA and other enterprises. He said:

“Expanding our partnership with ServiceNow is a key milestone in our mission to build the world’s leading AI-native services company,”  

“By combining ServiceNow’s agentic AI platform with NTT DATA’s global delivery scale and industry expertise, we’re enabling enterprises to accelerate innovation, enhance productivity, and achieve sustainable growth.” 

Who is NTT DATA?

The technology services company provides enterprises and governments with responsible innovations for cloud, AI, security, data centers, connectivity, and application services. 

This latest partnership allows NTT DATA to access ServiceNow’s generative AI and workflow automation, enabling it to supply improved offerings to its customers by integrating more complex solutions, positioning itself as a leader of enterprise AI transformation within the industry. 

NTT DATA can also use this opportunity to expand its market reach by co-developing AI tools with a well-established company, especially in the US and Europe, where ServiceNow holds strong brand recognition. 

What This Partnership Means

This partnership expansion reflects the increasing intensification of AI-led transformation investments amongst current major vendors. 

The collaboration allows both companies to become more central in their position as leaders in enterprise software strategy development, highlighting to other vendors where they stand to build better relationships instead of developing capabilities independently. 

By fully aligning operations such as products and delivery services, more companies can join the competition and adapt to trends cost-effectively. 

On Wednesday, the enterprise giant released its quarterly earnings report, reaching a total revenue of $3.407BN, a 22% increase. 

Away from the finances, the company also used the call to outline its commitment to expanding its AI-driven and CRM solutions. 

Transforming Solutions

As part of its plan to bolster AI across enterprises, ServiceNow has emphasized its goals to transform AI agents, customer relationship management, and return on investment results for customers.

AI Agents

During the call, ServiceNow execs discussed the company’s aim to transform AI for its customer enterprises through its real-time AI control tower, to monitor, track and govern its use. 

By using its configuration management leadership to help with AI governance under one system, enterprises can simplify their AI management and integration process to deliver faster ROI. 

Regarding its agents, ServiceNow has created its workflow ‘road map’ for them to function effectively across an enterprise and a tech stack, going from a simple chatbot to a complex AI tool. 

This also includes voice, text, image and data options to allow customers to unify their AI experience. 

The company expressed its vision for a fully hybrid workflow future, with human and AI agents working together to solve and complete customer issues, tasks and actions. 

In fact, the company reported a sharp increase in activity for its AI control tower in Q3, with more than 4 times the traffic volume quarter-over-quarter.  

This also included a 55x increase in AI Agent Assist consumption in the past five months. 

In conversation with CX Today, Simon Harrison, Analyst and Executive Partner at Actionary, explained how ServiceNow positions its agentic AI as a reliable automation. 

He said, “ServiceNow’s approach to Agentic AI is pragmatic and brings guardrails, governance, and visibility to what can otherwise be chaotic experimentation with AI agents. 

“The company’s strength lies in how its highly usable approach is anchored in a mature workflow and data model, making its version of Agentic AI more controllable, measurable, and enterprise-ready than most.”

With AI turning into the new user interface, ServiceNow introduced AI experience earlier in Q3, creating AI assistants with a unified interface for a more seamless experience. 

This move from traditional UI avoids the repeated manual research through workflow engines and isolated agents by replacing them with one interface for all actions. 

CRM Investment Expansion

To revamp the customer service market, ServiceNow aims to drive higher growth and loyalty by turning its CRM into an AI-first system of action. 

By reconstructing CRM to center on automation, it can unify enterprise departments to drive actionable outcomes as well as data tracking. 

This means that by delivering more specific, automated capabilities, the integrated AI can understand customer context to resolve issues. 

This is used in customer service, where AI agents can resolve issues of consumer dissatisfaction, flag risk cases, and remind teams to respond before SLAs are missed. 

It also allows agent-to-agent orchestration to deliver faster, qualitative results. 

ROI

As pointed out in the earnings call, ROI is often a failure for tech enterprises due to its poor integration. 

However, ServiceNow’s AI platform changes this outcome by working throughout departments and tech stacks. 

This speeds up enterprise deployment, automation, and payback times, allowing investment outcomes to arrive within quarters, rather than years. 

The AI agents and control towers also provide cost benefits for ROI with faster resolutions. 

Customer Results

ServiceNow’s third quarter has also benefited from its enterprise customer base, with 553 customers each achieving at least $5MN in ACV. 

This was followed by the group of customers who had generated over $50MN increasing by 20% year-over-year. 

The company has also teased a partnership expansion plan with CcaaS giant, Genesys to focus on unification for agent-to-agentic orchestration between their two respective AI-powered platforms. 

This will allow both companies’ customers to use these systems under one environment to deliver faster, autonomous customer service. 

Enterprise customers are also seeing their personal results from ServiceNow’s efforts this quarter. 

In one instance, the US Federal boosted strong results in Q3 after signing a OneGov agreement with ServiceNow, beating ACV expectations. 

This was contributed to by ServiceNow’s Now Assist AI’s agency conversion and their AI control tower’s success in governance outcomes, resulting in strong ROI payoffs. 

With this deal, ServiceNow can provide government-wide agencies with its products including its AI and workflow solutions, allowing more agencies to use ServiceNow due to faster implementation. 

In return, ServiceNow has estimated to save the federal government billions over the coming five years, by boosting its overall efficiency levels by 30%. 

Key Earnings Results

Below is a breakdown of some of ServiceNow’s key financial results for Q3 2025:

• In its third quarter, ServiceNow outmatches its earnings expectations, with an increase in total revenue of over $3.4BN. 
• Its top earning result, subscription revenues, saw a quarterly earning result of $3.299BN, a 21.5% year-on-year growth
• The company also expects to reach its new AI revenue target of $1BN in 2026, after already exceeding its $500MN target for the year

Between 15:45 UTC on October 29 and 00:05 UTC on October 30, configuration change caused node failures in Azure Front Door (AFD), Microsoft’s global, cloud-based service that handles content delivery and routing, according to Azure’s status page.

A whole host of Azure services experienced latencies, timeouts and errors, including Azure Communication Services (ACS). The voice and SMS messaging channels in Dynamics 365 Contact Center are built on top of ACS, which enables organizations to provision phone numbers, enable voice calls and manage SMS capabilities through ACS directly.

The outage disrupted customer services across multiple industries, including airlines, retail and gaming, all of which use Azure for their backend operations including point-of-sale systems, customer portals, and mobile apps.

Alaska and Hawaiian Airlines, which have recently merged, reported that the Azure hosts several of their key services, including their websites, which meant that customers were unable to book or check in for flights online.

Travelers who were unable to check in were advised to see an airport agent for their boarding pass and plan for additional time in the terminal, as there were long lines.

“Our teams worked quickly to stand up our backup infrastructure to allow our guests to book and check-in for their flights online while minimizing operational disruptions,” Alaska Airlines stated. The airline added that it would bring the affected systems back online “once Microsoft resolves the issue from its end.”

Heathrow Airport also reported problems with its website, while retailers like Starbucks, Costco, and Kroger experienced interruptions to their websites and mobile apps, indicated by spikes in reports on outage monitoring site DownDetector.

Microsoft’s own services were not immune, as its customers were unable to log in to Xbox Live, Minecraft, and other Microsoft gaming platforms, and access to 365 productivity tools like Outlook, Teams and SharePoint went offline for enterprise users as well as consumers.

The timing of the outage was ironic, given that Microsoft reported its quarterly earnings with its investor relations website down ahead of the analyst call.

The company reported 40 percent year-on-year growth in its Azure revenues, indicating how deeply entrenched the cloud infrastructure is across industries.

The outage served as a reminder of the critical role cloud infrastructure plays in modern customer service delivery and the risks of centralized dependencies.

Successive Outages Expose Systemic Dependence on Cloud Giants

While the AWS outage originated from Amazon’s servers in Northern Virginia, affecting the US East Coast and parts of Western Europe, the Azure outage spread further, with Downdetector indicating disruptions from parts of Asia as well as the U.S. and Europe.

Initial reports had suggested the outage was global. Vivek Dodd, CEO at Skillcast, told CX Today:

“Another outage following so closely after the recent disruption at AWS highlights just how dependent the economy has become on major technology providers.”

“When these big platforms experience downtime, the ripple effects are immediate and widespread across industries—disrupting financial systems, logistics networks, and retail operations.”

As digital transformation brings more enterprise systems into the cloud, many companies are struggling to establish resilience plans to keep up with the growing risks.

“The assumption that leading cloud platforms will always be available has left some enterprises exposed when outages occur,” Dodd said.

Enterprises need to proactively embed operational resilience and third-party risk management as core priorities to mitigate the risk, rather than being reactive and treating them as afterthoughts.

“Building true resilience requires more than technological redundancy; it demands foresight, planning and training,” Dodd said.

One way to do this is by avoiding full reliance on cloud infrastructure, by using hybrid approaches so that their systems have redundancies.

“Organizations should implement hybrid or multi-cloud models, such as diversifying across providers to avoid overreliance on a single vendor, establish clear crisis-response protocols and invest in company-wide compliance and resilience to handle these situations efficiently,” Dodd explained.

Because when third-party infrastructure goes down, it is the enterprise that suffers the impact on its customer experience.

“Incidents like this serve as a powerful reminder that resilience isn’t just about technology, it’s about protecting trust, productivity, and customer confidence in a digital-first economy.”

At around 03:11 EST (08:11 BST), AWS’s US-East-1 region began experiencing increased error rates and latencies, according to the AWS service health page.

The initial internal DNS failures caused a cascade of disruptions across services from enterprise SaaS to messaging, banking, education, and even smart home systems. While Amazon applied a fix, API problems resulted in a wave of secondary outages.

It served as a reminder that infrastructure failures still translate to customer frustration — and, more importantly, a sudden loss of trust.

When everyday services like banking apps, smart devices, and communication tools stop working, users don’t think about DNS errors or data center regions; they just know something they rely on has failed them.

Users of social and messaging platforms like Snapchat, Signal and Reddit quickly flooded outage trackers with reports of frozen feeds and error messages.

The disruption soon rippled into more critical sectors. UK customers of Lloyds and Halifax couldn’t log into their accounts or complete transactions, while users of Amazon’s own Ring doorbell and camera were left staring at unresponsive devices.

Even education and enterprise tools weren’t spared. Universities like Rutgers reported degraded performance across learning portals, Zoom and Adobe platforms.

Together, the incidents underscored just how deeply everyday digital life depends on cloud reliability, from morning meetings to mobile payments and multiplayer games.

By mid-morning in the EST time zone, Amazon’s website reported 36 of its services were back up and running, including Amazon Connect, but another 72 were still interrupted.

“We have applied multiple mitigations across multiple Availability Zones (AZs) in US-EAST-1 and are still experiencing elevated errors for new EC2 instance launches,” the company stated.

The update signaled that even as services began to recover, new workloads and restarts remained unstable, a clear sign of how deeply the issue had rippled through the system.

“Similar failures have been common causes for major outages in the past, and usually stem from incorrect, updated configurations, or due to poor monitoring of expiration timelines for configurations, certificates, etc.,” said Aras Nazarovas, Senior Security Researcher at Cybernews.

“From initial reporting there are no indications of any security breach, however failing to keep information or resources available for clients can be classified as a cyber incident, even if there was no malicious outsider or malicious intent.”

Nazarovas noted that, while not malicious in nature, such configuration-related missteps can affect the customer experience for thousands of businesses.

Similar outages occur almost every year, and they can be a reminder of how extensive software supply chains have become, showing how a simple issue on a handful of Amazon Data Centers caused thousands of issues to their clients… in worst case scenarios such an outage could have had serious consequences in critical infrastructure sectors.

The outage also highlights the importance of disaster preparedness in coordinating recovery and maintaining communication with customers, Nazarovas said.

“In the event of such disruptions, users should immediately seek alternative solutions for communication (different app, phone calls, SMS, radio) to be able to coordinate next steps towards recovering from such a disruption. It is a good practice to have a ‘Disaster Recovery Plan’ where alternative communication channels and other critical steps have been planned in advance.”

The mood on social media was equal parts frustration and humor. Users churned out memes such as “And this is why everyone using the same damn Amazon web services is a great idea” and a graphic showing all the sites that depend on AWS.

But the humor reflected a broader commentary on how heavily enterprises depend on a handful of cloud providers.

The incident offers several clear lessons. Downtime translates directly into customer frustration. When users cannot access the services they expect, the perception is immediate.

And trust is fragile. If a bank customer trying to log in at 09:00 finds “service unavailable”, trust erodes. Customers of highly sensitive services like banking expect 100% uptime. Even if it is not caused by the bank’s own systems, an outage still hits its bank reputation.

The fact that an infrastructure outage (DNS/DynamoDB endpoint in US-EAST-1) affected downstream services brings home that indirect dependencies matter when it comes to customer experience and their perception of a service provider.

Communication is key for the customer. Some services were quick to post status updates, while others were not. Having a clear communication plan is now a core part of providing a highly-regarded experience.

Enterprises should know where their dependencies are and have updated contingency plans. They should also expect issues such as failed payment authorizations and spikes in customer support contact for days or even weeks after such an outage.

Recent cyber attacks on Jaguar Land Rover and Stellantis have exposed how vulnerable the sector is in its ability to deliver on the customer experience it promises to the consumers and business clients across its sprawling supply chain.

Typically, the conversation in automotive CX centers on showroom experience, mobile apps, and increasingly, infotainment systems. But behind the scenes, a vast B2B ecosystem powers the industry: OEMs, Tier 1 suppliers, dealerships, fleet operators, and logistics partners all rely on secure digital infrastructure to manage their relationships and keep things moving.

These business customers expect seamless access to portals, real-time order tracking, and reliable service delivery. When a cyberattack hits, the effects reverberate through a vast B2B ecosystem, touching business partners whose operations depend on trust and uptime.

“The recent cybersecurity breaches at Jaguar Land Rover and Stellantis highlight the threats that can disrupt the modern automotive supply chain,” Jeff Collins, CEO of WanAware told CX Today.

“These attacks underscore the significant vulnerabilities inherent in the industry’s vast web of interconnected software and service partners. Together they reveal a critical industry-wide exposure; the automotive ecosystem is not only susceptible to production-halting attacks on core manufacturing but also to data breaches through its extended digital supply chain, eroding confidence, necessitating a more holistic and collaborative security strategy.”

Stellantis stated on September 21 that it had recently detected “unauthorized access to a third-party service provider’s platform that supports our North American customer service operations.”

The personal customer information involved was limited to contact information, the company said. “Importantly, the affected platform does not store financial or sensitive personal information, and none was accessed.” Stellantis notified the appropriate authorities and informed affected customers directly.

The incident raised alarms about third-party risk and the fragility of integrated platforms that underpin B2B relationships.

Jaguar Land Rover faces a different kind of breach, the effects of which are still ongoing. The automaker was hit by a cyberattack in late August, which forced the company to shut down its IT networks and suspend production at its factories in the UK, Slovakia, Brazil and India.

The company initially said there was no evidence that customer data had been stolen, but later stated that “we now believe that some data has been affected.”

The impact of the attack was so extensive that the company halted production on September 1 and subsequently delayed its restart into October, a symptom of the increasingly interconnected and automated approach to car manufacturing that can make it difficult to isolate individual systems.

The disruption has spread far beyond JLR’s factory floors. Suppliers have reported cancelled orders and delayed payments, and dealers have been left unable to access parts ordering systems or complete customer transactions.

JLR set up a help desk for suppliers and has been trying to share information on the extent of its supply chain, which may include more than 700 companies manufacturing the 30,000 parts that can make up a luxury car, the Guardian reported.

For instance, JLR is the main customer of Autins, an automotive insulation supplier, and the production halt “has had a material effect” on its operations, the company stated in its trading update on September 17.

Cando Wango, National Cybersecurity Solutions Architect at AllCovered, the IT services division of Konica Minolta, told CX Today:

“It was startling to learn that Jaguar was brought to a complete standstill a full month after its breach, with projections of another month of downtime to follow—losses compounding without a clear resolution in sight.”

“It raised pressing questions: Had their incident response plan been tested? Were disaster recovery drills conducted? Were their recovery time objectives (RTOs) and recovery point objectives (RPOs) clearly defined? It is difficult to comprehend how an organization of such stature and history could be left so exposed.”

JLR announced a phased restart of its manufacturing operations starting at its facilities in the West Midlands, UK, as well as plants in Castle Bromwich, Halewood and Solihull, UK, and Slovakia. “Further updates on the next steps of the controlled, phased restart will follow,” the company said. This gradual return to production highlights the extent of disruption caused by the cyber attack, suggesting that the incident affected critical operational systems and supply chain coordination.

The Ripple Effect Across the Supply Chain

“Automotive manufacturers have become as much software as transportation companies, facing all the challenges inherent to software security,” according to a report by professional transport association SAE International.

While automakers still produce some equipment, their focus is increasingly on research and development, supply chain management, and final product assembly, all of which are managed by multi-layered software systems.

A staggering 84% of respondents to an SAE survey said that they were concerned cybersecurity practices are not keeping pace with evolving technologies in the industry, and 73% expressed concern about the cybersecurity posture of automotive technologies supplied by third parties. And 63% test less than half of hardware, software, or other technologies for vulnerabilities.

Cyber attacks on automotive companies don’t just cause temporary headaches—they trigger a cascade of CX failures along the supply chain.

• Customer portals or connected vehicle services can be disrupted, affecting clients’ business operations and eroding trust.
• Suppliers and dealerships can lose access to key systems like inventory and order management, throwing off delivery schedules and service appointments.
• Missed service-level agreements (SLAs) and late deliveries can come with financial penalties, strained partnerships, and pressure to renegotiate contracts.
• Fleet managers and logistics companies depend on connected platforms for real-time tracking and diagnostics. If those systems are breached or go offline, fleets can be left in the dark.
• Businesses can suffer reputational damage if their clients perceive a lack of transparency or resilience in crisis response, prompting them to reconsider relationships.

“This incident also highlights broader industry and supply chain concerns. Is this an isolated case, or a warning sign of what’s to come?” Wango said. ”If Jaguar’s experience is any indication that the automotive sector is a “glass house,” then we may soon see more cracks—and eventually shattered glass. Threat actors are opportunistic; once they spot vulnerabilities, they move quickly to exploit them.”

Cybersecurity is no longer just an IT concern; it’s a core component of customer experience. Business clients want to know that their data is safe, their operations won’t be disrupted, and that contingency plans are in place.

Recovery is a CX Strategy

Jonathon Ellison, NCSC Director of National Resilience, highlighted in a recent blog post that beyond prevention, recovery hinges on preparation:

“The organizations that handle incidents best are the ones that have rehearsed them. They understand what they need to do to keep their operations going without some or all of their technology estate.”

Enterprises should know their IT systems inside and out, conduct impact assessments, define roles, establish communication plans, and regularly run incident response exercises.

The NCSC also highlights the importance of collaboration and transparency across industries. By participating in sector-wide information-sharing groups and being open about cyber incidents and lessons learned, organizations can collectively strengthen their resilience and better protect the wider business ecosystem.

Once a security breach has occurred, it is important that a company not simply breathe a sigh of relief and move on. Recovery involves more than patching systems. Rebuilding relationships requires transparent communication with affected partners, restoration of services and access as quickly as possible, and clear timelines and accountability.

And it is crucial that the company make long-term improvements in data governance and third-party oversight.

Stellantis made the right moves in the immediate aftermath of its attack: “Upon discovery, we immediately activated our incident response protocols, initiated a comprehensive investigation, and took prompt action to contain and mitigate the situation,” the automaker stated. “We encourage customers to remain vigilant against potential phishing attempts and avoid clicking on suspicious links or sharing personal information in response to unexpected emails, texts, or calls.”

This is key, as malicious actors that have customer data in hand can use it to conduct phishing and social engineering attacks, as well as identity theft.

Cybersecurity as a Differentiator

As automotive companies continue to digitize, from connected vehicles to cloud-based supply chains, cybersecurity will become a key differentiator in B2B CX. Vendors and OEMs that can demonstrate robust data protection, secure integrations and resilience in the face of threats will stand out.

“In my recent work with organizations across industries, one fact has become increasingly clear: cybersecurity is the defining challenge of our era,” Wango said.

A strong security posture must be comprehensive, coordinated, integrated, and continuously optimized. Just as importantly, organizations must ensure they are not seen as “low-hanging fruit” for attackers. Given the extensive dialogue in recent years around cyber resilience, it is astonishing that any enterprise could overlook these fundamentals so completely.

“I hope this serves as a wake-up call across industries: cutting corners on cybersecurity does not save money—it only accelerates risk and, ultimately, puts the future of the business at stake.”

Anthropic is positioning Haiku 4.5 as a faster, more economical counterpart for real-time use cases. As the company put it: “What was recently at the frontier is now cheaper and faster.”

Claude Haiku 4.5 offers similar coding performance to Sonnet 4, which was state-of-the-art just five months ago, but “at one-third the cost and more than twice the speed,” the company stated. Haiku 4.5 surpasses Sonnet 4 at certain tasks, like using computers, which can make applications like the Claude for Chrome assistant faster.

That kind of efficiency is key for AI-driven customer experience, where responsiveness and cost management are often at odds. From conversational chatbots and real-time support agents to background automation that powers service workflows, AI systems in CX need to think quickly without breaking the budget. The company noted:

Users who rely on AI for real-time, low-latency tasks like chat assistants, customer service agents, or pair programming will appreciate Haiku 4.5’s combination of high intelligence and remarkable speed.

Developers using Claude Code will find coding multiple-agent projects and rapid prototyping more responsive, enabling smoother, faster iteration for developers building customer service agents.

With its recent model releases, Anthropic has been making a broader push toward serving enterprise customers. Over the past year, the company has deepened integrations with major cloud platforms like Amazon Bedrock and Google Cloud’s Vertex AI, making its models easier to deploy at scale.

This expansion signals Anthropic’s intent to position Claude not just as a research model, but as a core productivity tool for businesses looking to embed AI across customer experience operations. By focusing on enterprise-ready reliability and flexible pricing, Anthropic is targeting organizations that need both high performance and predictable costs as they scale their AI initiatives.

The company recently announced plans to increase its customer support staff fivefold this year. It now holds the largest market share in enterprise AI, having grown from fewer than 1,000 business customers two years ago to over 300,000 globally, as demand for its Claude models accelerates across industries.

To support this expansion, the company is tripling its international workforce and expanding its Applied AI team, which embeds staff within client organizations to help them build new tools and workflows on top of Claude.

While Claude is widely recognized for its advanced coding assistant capabilities, making it a favorite among developers, Anthropic’s enterprise strategy increasingly targets a broader range of users, from customer experience teams to business operations leaders seeking smarter, faster automation.

Bridging the Performance Gap

Companies deploying AI in customer support have had to weigh up using a large, expensive model that can reason deeply, or a smaller, faster one that can’t always keep up with complex tasks. Haiku 4.5 could ease that compromise.

Jeff Wang, CEO of Windsurf, captured this shift:

Historically, models have sacrificed speed and cost for quality. Haiku 4.5 is blurring the lines on this trade-off: it’s a fast frontier model that keeps costs efficient and signals where this class of models is headed.

Anthropic envisions multi-model orchestration, where the larger Sonnet 4.5 can plan complex tasks, while Haiku 4.5 executes subtasks in parallel. That offers a potentially powerful setup for customer service operations handling high call volumes or simultaneous customer interactions.

Companies scaling automated customer interactions could create chatbots that feel less like bots and service experiences that don’t lag when customers need quick answers.

Early testers in the developer community have found the small model to be effective.

At Shopify, Staff Engineer Ben Lafferty said, “Haiku 4.5 delivers intelligence without sacrificing speed, enabling us to build AI applications that utilize both deep reasoning and real-time responsiveness.”

Andrew Filev, CEO of Zencoder, noted how far small models have come: “Haiku 4.5 is remarkably capable—just six months ago, this level of performance would have been state-of-the-art on our internal benchmarks. Now it runs 4–5 times faster than Sonnet 4.5 at a fraction of the cost, unlocking an entirely new set of use cases.”

Claude Haiku 4.5 is available now via Claude Code and the Anthropic API, as well as on Amazon Bedrock and Google Cloud’s Vertex AI. For enterprise buyers, that broad accessibility means lower integration friction and more flexible pricing models across major cloud providers.

The launch points to a shift in how AI will be deployed across customer-facing systems, where real-time responsiveness is becoming a baseline expectation and cost efficiency no longer requires compromising on quality.