In the race to operationalize AI in sales and marketing, data—not algorithms—is proving to be the real differentiator. ZoomInfo just got a strong endorsement of that idea.

The company has been named a Leader in The Forrester Wave™: Marketing and Sales Data Providers for B2B, Q1 2026 by Forrester, earning top marks across key categories and reinforcing its position as a central player in the go-to-market (GTM) tech stack.

The report doesn’t just recognize ZoomInfo’s current footprint—it points to where the market is heading: toward unified data platforms that power AI-driven sales and marketing workflows.

A Leader in a Crowded, High-Stakes Category

B2B data providers have become foundational to modern revenue operations. From prospecting to personalization, nearly every GTM function now depends on accurate, unified data.

According to Forrester, ZoomInfo stands out for both scale and ambition:

• Highest score in the current offering category among evaluated vendors

• Top scores in 20 of 27 criteria, including data foundation and platform ecosystem

• Perfect scores in strategy areas like vision, innovation, and partner ecosystem

That combination—strong execution today and a clear roadmap forward—is what typically separates Leaders from the pack in Forrester’s evaluations.

The Real Story: Data as AI Infrastructure

The most interesting takeaway isn’t the ranking—it’s why ZoomInfo earned it.

Forrester specifically highlighted the company’s data collection, identity resolution, and GTM knowledge graph, calling it a “technology standard” and noting its relevance for agentic AI use cases.

That last point matters.

As AI tools evolve from assistants to autonomous agents, they need structured, reliable data to operate effectively. Without it, even the most advanced models fall short.

ZoomInfo’s strategy centers on becoming that data backbone—an underlying layer that powers:

• Lead generation and enrichment

• Account-based marketing

• Sales intelligence and forecasting

• AI-driven insights and automation

In other words, less a tool—and more infrastructure.

From Sales Data Vendor to GTM Platform

For years, ZoomInfo was primarily seen as a sales data provider. That’s changing.

Forrester notes the company has “entrenched itself as the default data provider for B2B sales,” but is now expanding into a full GTM ecosystem—spanning both marketing and sales functions.

This shift reflects a broader convergence in the MarTech and SalesTech landscape:

• Marketing and sales data are merging into unified customer profiles

• Revenue teams are aligning around shared platforms

• AI is driving demand for centralized, high-quality data sources

ZoomInfo’s platform approach positions it to compete not just with data vendors, but with larger ecosystem players aiming to own the entire GTM workflow.

Betting Big on AI—and the Data Behind It

ZoomInfo’s leadership is also leaning heavily into AI, particularly generative and agentic use cases.

The company claims early-mover advantage with genAI capabilities for data capture and insight generation, backed by a significant investment—nearly $200 million annually in R&D and data infrastructure.

That level of spend underscores a key industry reality: AI innovation is increasingly tied to data ownership and quality, not just model development.

The GTM knowledge graph—a structured data layer designed to connect entities, relationships, and signals—is central to that vision. It’s what enables AI systems to move from surface-level insights to context-aware decision-making.

Why This Matters for B2B Teams

For B2B organizations, the implications are straightforward:

• Better data → more accurate targeting

• Unified platforms → less tool fragmentation

• AI-ready infrastructure → faster adoption of automation

But there’s also a strategic shift underway. Companies are no longer just buying tools—they’re investing in data ecosystems that can support long-term growth and AI integration.

ZoomInfo’s positioning aligns directly with that trend.

The Competitive Angle

ZoomInfo isn’t alone in this space. Competitors ranging from legacy data providers to newer AI-native platforms are all vying for control of the GTM data layer.

What gives ZoomInfo an edge—for now—is its combination of:

• Scale in B2B contact and company data

• Integrated platform capabilities

• Early investment in AI and knowledge graph infrastructure

The challenge will be maintaining that lead as competitors accelerate their own AI and data strategies.

The Bottom Line

ZoomInfo’s Leader ranking in the latest Forrester Wave is less about recognition and more about validation of a broader shift: data is becoming the foundation of AI-driven go-to-market strategies.

As sales and marketing teams adopt more autonomous tools, the platforms that can provide clean, connected, and actionable data will define the next phase of competition.

Right now, ZoomInfo is making a strong case that it intends to be one of them.

Get in touch with our MarTech Experts.

Aurora Mobile Limited is planting a flag in one of Asia’s most demanding tech markets. The company has announced the launch of Aurora Mobile Japan K.K., marking its official entry into Japan and bringing its AI-driven engagement platform, EngageLab, directly to local enterprises.

The move is less about geographic expansion and more about timing. As Japanese companies push deeper into global markets, the pressure to unify customer data, streamline engagement, and prove ROI is intensifying. Aurora Mobile is betting its full-stack, AI-powered approach can help close that gap.

A Unified Play for Fragmented Customer Journeys

Customer engagement in large enterprises is often messy—split across channels, tools, and teams. Aurora Mobile’s pitch with EngageLab is to consolidate that sprawl into a single AI-driven ecosystem.

The platform combines:

• Omnichannel messaging (AppPush, WebPush, email, SMS, WhatsApp)

• AI-powered customer service agents

• Built-in identity verification and security tools

The goal is to move beyond campaign execution into what the company calls a “full-journey AI engagement” model—where acquisition, interaction, support, and security are tightly integrated.

That’s increasingly where the MarTech market is heading. Platforms are evolving from point solutions into end-to-end customer lifecycle systems, often layered with AI to automate decision-making.

Why Japan—and Why Now

Japan presents a unique mix of opportunity and constraint.

On one hand, it’s a mature, high-value market with strong enterprise adoption of digital tools. On the other, it faces structural challenges—most notably labor shortages and operational inefficiencies—that make automation especially attractive.

Aurora Mobile is leaning into both dynamics:

• Helping enterprises scale globally with better customer lifecycle management

• Using AI to reduce operational overhead, particularly in customer support

CEO Weidong Luo framed the expansion around precision and performance—two qualities Japanese enterprises tend to prioritize heavily.

The Three-Pillar Strategy

Aurora Mobile Japan K.K. is launching with a modular suite built around three core pillars:

1. Omnichannel Marketing, Optimized by AI

EngageLab unifies multiple communication channels into a single system capable of delivering notifications at scale. More importantly, it adds intelligence:

• Drag-and-drop journey builder for campaign orchestration

• Algorithms that optimize send times and channels

• Proprietary delivery tech claiming higher success rates than industry norms

The emphasis here isn’t just reach—it’s efficiency and conversion, a growing priority as marketing budgets face tighter scrutiny.

2. AI Customer Support That Cuts Costs

Through its LiveDesk solution, Aurora Mobile is targeting one of Japan’s biggest pain points: customer service staffing.

• AI agents can reportedly handle up to 90% of inquiries

• Operational costs reduced by as much as 70%

• Seamless escalation to human agents for complex cases

This hybrid model—AI-first, human-assisted—is quickly becoming the standard across customer experience platforms.

3. Security Without Friction

Security tools are often necessary but intrusive. Aurora Mobile is trying to flip that narrative with:

• Silent authentication for seamless user verification

• OTP services with high delivery success rates

• AI-powered CAPTCHA to block bots without disrupting users

The idea: make security invisible to legitimate users while still robust enough to prevent fraud.

Local Presence, Local Expectations

Aurora Mobile isn’t just exporting technology—it’s building a local operation. Aurora Mobile Japan K.K. will include a dedicated team offering consulting and technical support tailored to Japanese enterprises.

That’s a critical move. Japan’s market is notoriously difficult to penetrate without on-the-ground expertise, particularly when it comes to enterprise software adoption and integration.

The Competitive Landscape

Aurora Mobile enters a crowded space dominated by global MarTech platforms and regional players. Companies like Salesforce, Adobe, and local Japanese vendors already offer strong customer engagement and automation tools.

What differentiates Aurora Mobile is its attempt to bundle engagement, AI support, and security into a single platform—rather than treating them as separate layers.

Whether that integrated approach resonates will depend on execution, especially in a market that values reliability and precision over rapid experimentation.

The Bottom Line

Aurora Mobile’s Japan launch is a calculated bet on convergence—bringing marketing, customer experience, and security into a unified AI-driven system.

For Japanese enterprises navigating global expansion and operational challenges, that promise is compelling. But as always in MarTech, the real test will be whether integration translates into measurable business outcomes.

Get in touch with our MarTech Experts.

Digital transformation isn’t dead—but the way enterprises approach it is changing fast. AppsTek Corp is the latest services player to pivot, unveiling a strategic rebrand built around a new positioning: “Engineering the Digital Core.”

The message behind the rebrand is clear: enterprises no longer need one-off transformation projects—they need integrated, AI-ready foundations that tie together data, systems, and workflows.

It’s a subtle shift in language, but a significant one in strategy.

From Projects to Platforms

For more than a decade, AppsTek operated under the banner of “Transforming Ideas into Digital Realities,” focusing on building digital platforms and executing modernization initiatives.

That model still works—but it’s increasingly incomplete.

As enterprise environments grow more fragmented—spanning cloud, on-prem systems, multiple data pipelines, and now AI layers—companies are struggling with integration, not innovation. The result: disconnected systems, siloed data, and AI initiatives that never scale.

AppsTek’s new positioning reflects that reality. Instead of delivering standalone projects, the company is now emphasizing end-to-end architecture—what it calls the “digital core.”

What “Engineering the Digital Core” Actually Means

At its core (no pun intended), the strategy revolves around three pillars:

• Unifying platforms: Connecting disparate systems into a cohesive architecture

• Integrating data: Breaking down silos to enable real-time insights

• Embedding AI: Making intelligence part of everyday workflows, not an add-on

In practice, that means re-engineering legacy systems while designing scalable, AI-ready infrastructure that can evolve over time.

It’s a play that aligns closely with broader enterprise trends. As AI adoption accelerates, companies are realizing that AI is only as effective as the infrastructure beneath it—a theme echoed by larger players like Cisco and NVIDIA in their push for full-stack AI environments.

A Branding Refresh With Strategic Intent

The rebrand isn’t just conceptual—it comes with a refreshed visual identity.

AppsTek’s updated logo retains its original “A” while introducing sharper, more structured elements meant to signal architectural precision and forward momentum. The new color palette leans into themes of energy and technological depth—standard fare for tech rebrands, but aligned with the company’s shift toward systems-level thinking.

More interesting is what the branding represents internally: a repositioning of AppsTek from a delivery partner to a strategic architecture player.

Why This Shift Matters

AppsTek’s move reflects a broader recalibration happening across the IT services and digital engineering space.

Enterprises are moving beyond:

• Isolated digital transformation initiatives

• Short-term modernization projects

• Tool-first approaches to AI adoption

And toward:

• Platform-centric architectures

• Data-first strategies

• Embedded AI across business processes

This shift is forcing service providers to rethink their value proposition. It’s no longer enough to implement technology—clients expect partners to design the underlying systems that make AI and automation sustainable.

Competing in a Crowded Market

AppsTek isn’t alone in chasing this narrative. Larger firms like Accenture, Cognizant, and Thoughtworks have been pushing similar ideas around platform engineering and AI-native architectures.

The challenge for mid-sized players is differentiation.

AppsTek’s angle appears to be focus: positioning itself specifically around the “digital core” as the foundation for agility and long-term growth, rather than trying to cover every aspect of digital transformation.

Whether that resonates will depend on execution—and the company’s ability to demonstrate measurable outcomes beyond the rebrand.

The Bottom Line

AppsTek’s “Engineering the Digital Core” rebrand is more than a marketing refresh—it’s a signal of where enterprise technology priorities are heading.

As AI becomes central to business strategy, the real work is shifting beneath the surface: rebuilding the core systems that make intelligence scalable, secure, and sustainable.

For service providers, that means moving up the value chain. For enterprises, it means rethinking transformation as architecture—not just implementation.

Get in touch with our MarTech Experts.

Enterprise AI has a scaling problem. Plenty of pilots, not enough production—and too many disconnected systems in between. Cisco and NVIDIA want to change that.

The two companies have announced a major expansion of their Secure AI Factory initiative, positioning it as a full-stack framework for deploying AI across core data centers and edge environments—with security baked in from silicon to software.

The goal: help enterprises move from experimentation to real-world deployment in weeks, not months, while avoiding the integration headaches that often stall AI projects.

AI Moves to the Edge—And Infrastructure Has to Follow

One of the biggest shifts driving this update is where AI actually runs.

Inference—where models generate predictions or decisions—is increasingly happening outside centralized data centers, closer to where data is created. Think hospital floors, retail stores, or factory lines where latency matters and decisions can’t wait.

Cisco and NVIDIA are leaning into that reality with expanded edge capabilities:

• Support for NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs across Cisco UCS and edge platforms

• New reference architectures for service providers via the Cisco AI Grid

• Integration with Cisco’s Mobility Services Platform for carrier-grade AI services

The pitch is simple: bring AI to the data, not the other way around.

That’s especially relevant as industries push toward real-time analytics, autonomous systems, and AI-driven operations—all of which depend on low-latency processing at the edge.

Faster Builds, Bigger Pipes

Beyond edge computing, Cisco is also targeting one of the biggest bottlenecks in AI infrastructure: network performance and deployment complexity.

The expansion introduces new high-performance networking hardware, including:

• Cisco N9100 switches delivering up to 102.4 Tbps throughput, powered by NVIDIA Spectrum-6 silicon

• 800G switching support for high-bandwidth AI workloads

• Integration into Cisco Nexus One and Nexus Hyperfabric for simplified deployment

If that sounds like overkill, it’s not. Large-scale AI workloads—especially those involving distributed training or real-time inference—are incredibly network-intensive. Bottlenecks at the network layer can cripple performance.

Cisco’s approach is to treat networking as a first-class component of AI infrastructure, not an afterthought.

Two Paths to Building AI “Factories”

For organizations building large-scale AI environments—what NVIDIA often calls “AI factories”—Cisco is offering two validated deployment models:

1. A reference architecture aligned with NVIDIA’s Cloud Partner program

2. A Cisco-native cloud architecture built on its Silicon One platform

Both aim to reduce the need for custom integration, a common pain point for enterprises stitching together multi-vendor stacks.

This reflects a broader industry trend: pre-validated, modular architectures are becoming the default for AI deployments, replacing bespoke builds that are costly and slow to scale.

Security Moves Front and Center

If there’s one theme running through this announcement, it’s security.

As AI systems become more autonomous—particularly with the rise of AI agents—attack surfaces expand. Models, data pipelines, and even agent-to-agent interactions introduce new risks.

Cisco is embedding security across multiple layers:

Infrastructure Security

• Cisco Hybrid Mesh Firewall enforces policies across networks and workloads

• Extended to NVIDIA BlueField DPUs for server-level threat blocking

• Designed to stop threats before they reach sensitive data

AI Model and Agent Security

• Cisco AI Defense adds vulnerability testing and model protection

• Integration with NVIDIA NeMo Guardrails to manage AI behavior

• New controls for securing agent interactions, especially at the edge

Agent Runtime Protection

• Support for NVIDIA OpenShell runtimes

• Continuous monitoring of agent actions to prevent misuse or unintended behavior

The message is clear: in the “agentic AI” era, security can’t be bolted on later—it has to be embedded from the start.

Why This Matters Now

The timing aligns with a broader shift in enterprise AI.

According to analysts like IDC, companies are moving past the “what can AI do?” phase and into “how do we operationalize it?” That shift brings new challenges:

• Scaling infrastructure efficiently

• Managing distributed workloads

• Securing increasingly autonomous systems

• Avoiding vendor fragmentation

Cisco and NVIDIA are positioning Secure AI Factory as a solution to all four—essentially offering a blueprint for enterprise AI at scale.

The Bigger Competitive Landscape

Cisco isn’t alone in this push. Hyperscalers and infrastructure players—from AWS to Microsoft Azure—are also racing to provide end-to-end AI stacks.

What differentiates Cisco’s approach is its focus on networking, edge infrastructure, and security integration—areas where it already has deep enterprise penetration.

By partnering closely with NVIDIA, the dominant force in AI hardware, Cisco is strengthening its position in a market increasingly defined by full-stack ecosystems rather than standalone products.

The Bottom Line

Cisco and NVIDIA’s expanded Secure AI Factory is less about launching new hardware and more about reducing friction in enterprise AI adoption.

By combining high-performance networking, edge-ready infrastructure, and embedded security, the companies are trying to solve a persistent problem: turning AI from a promising pilot into a scalable, secure, production system.

For enterprises under pressure to show ROI on AI investments, that shift—from experimentation to execution—may be the most important upgrade of all.

Get in touch with our MarTech Experts.

Dropshipping has long promised low-barrier ecommerce—but running a profitable store still requires a surprising amount of manual work. Doba thinks AI can fix that.

The company has launched Doba Pilot in beta, positioning it as the industry’s first AI-powered “Dropshipping Agent”—a conversational tool that can build, manage, and scale an online store using natural language prompts. Instead of juggling dashboards, integrations, and spreadsheets, users can simply describe what they want, and the system handles the execution.

It’s a familiar pitch in the age of AI copilots—but applying it end-to-end across ecommerce operations is a notable step forward.

From Idea to Storefront—By Typing a Sentence

At its core, Doba Pilot acts like an ecommerce operator you can talk to.

A user might type: “Build a store, pick trending outdoor products, and list them with a 20% margin.” From there, the platform kicks off a multi-step workflow:

• Store setup (typically on Shopify)

• Product sourcing based on demand and pricing signals

• AI-generated product listings with descriptions and pricing

• Inventory syncing across suppliers in real time

The key difference isn’t any single feature—it’s that the system handles the entire workflow, not just isolated tasks.

That’s where Doba is trying to stand apart. Most dropshipping tools focus on one layer—supplier access, listing automation, or fulfillment. Doba Pilot bundles all of it into a single AI-driven flow.

The Rise of the “AI Agent” in Ecommerce

Doba Pilot lands squarely in one of 2026’s biggest tech trends: AI agents.

Unlike traditional automation tools, agents are designed to interpret intent and execute multi-step processes autonomously. In ecommerce, that means moving beyond “assistive” features (like copy generation) toward systems that can actually run parts of the business.

We’re already seeing similar moves across SaaS:

• AI copilots embedded in CRM and marketing platforms

• Autonomous workflows in customer support and analytics tools

• Generative AI layered into product and merchandising systems

Doba’s bet is that dropshipping—often used by solo founders and small teams—is especially suited for this model. The fewer people involved, the more valuable end-to-end automation becomes.

What Doba Pilot Actually Does

The beta version focuses on four core capabilities:

1. AI Product Discovery
Analyzes demand trends, pricing potential, and supplier data to surface “winning” products.

2. Automated Store Setup
Helps users quickly configure a storefront, with a strong emphasis on Shopify integration.

3. AI-Generated Listings
Creates product descriptions, pricing suggestions, and structured item details optimized for search and conversion.

4. Real-Time Inventory Sync
Keeps product availability aligned across suppliers and storefronts—one of the more error-prone aspects of dropshipping.

All of this is powered by Doba’s existing supplier marketplace, which includes a network of primarily U.S.-based fulfillment partners. That infrastructure is critical: without reliable sourcing and logistics, even the best AI layer falls apart.

Why This Matters for Ecommerce

Doba Pilot is less about adding new features and more about collapsing complexity.

Launching a dropshipping store typically involves:

• Choosing products

• Evaluating suppliers

• Setting up a storefront

• Writing listings

• Managing inventory and pricing

Each step has tools—but stitching them together is where most beginners struggle. By turning that process into a conversational workflow, Doba is effectively lowering the operational barrier.

For experienced sellers, the value shifts from access to speed and scale. Automating repetitive tasks could free up time for higher-impact work like branding, customer acquisition, and retention.

The Catch: Execution Still Matters

As with most AI-driven platforms, the promise is compelling—but the outcome will depend on execution.

Key questions remain:

• How accurate is the product selection logic?

• Can AI-generated listings actually convert?

• How well does the system handle edge cases like supplier delays or pricing volatility?

Dropshipping margins are notoriously thin, so even small inefficiencies can erode profitability. An AI agent that accelerates setup but misses on product-market fit won’t move the needle.

What’s Next

Doba says the beta phase will focus on user feedback, with plans to expand the platform into a more comprehensive AI assistant.

Future updates are expected to include:

• Deeper product intelligence and trend forecasting

• Enhanced automation for day-to-day operations

• Tools for compliance, IP risk detection, and inventory monitoring

In other words, the company is aiming to evolve Doba Pilot from a setup tool into a full lifecycle ecommerce agent.

The Bottom Line

Doba Pilot reflects a broader shift in ecommerce tooling—from dashboards to dialogue.

If the platform delivers on its promise, it could make dropshipping more accessible to newcomers while giving experienced sellers a faster path from idea to execution. But like any AI agent, its real value will depend on how well it performs in the messy, real-world dynamics of online retail.

For now, it’s an ambitious step toward a future where running an ecommerce business might be as simple as having a conversation.

Get in touch with our MarTech Experts.

The UK’s well-known Festival of Marketing is going global—and it’s starting with Asia.

Haymarket Media Asia, publisher of Campaign, has announced the launch of Festival of Marketing Asia (FoM Asia), set for September 3, 2026, at PARKROYAL COLLECTION Kuala Lumpur. The move marks the first regional expansion of the franchise since Haymarket acquired it from Centaur Media in 2025.

If the UK edition is anything to go by—drawing over 1,000 marketers annually—FoM Asia is aiming to become a cornerstone event for the region’s marketing leadership. But instead of scaling up, the organizers are deliberately keeping things tight, focused, and senior.

A Smaller, Sharper Marketing Event

Unlike sprawling multi-day conferences, FoM Asia is launching as a single-day event—a design choice that feels less like a constraint and more like a response to executive fatigue.

The target audience: mid- to senior-level marketers, including CMOs, strategy leaders, and MarTech decision-makers. The goal isn’t volume; it’s relevance.

That positioning reflects a broader shift in the events space. As marketing leaders juggle AI transformation, data privacy pressures, and ROI scrutiny, there’s growing demand for high-signal, low-noise gatherings—events that deliver actionable insights rather than keynote overload.

Built Around Asia’s Marketing Reality

What differentiates FoM Asia from simply exporting a UK format is its localized agenda.

An advisory board of senior marketers from brands like Mastercard, McDonald's Malaysia, Unilever, Schneider Electric, and Standard Chartered is shaping the program. That mix spans B2C and B2B, reflecting the increasingly blurred lines between the two disciplines.

It’s a notable move. Many global marketing events struggle with regional nuance; FoM Asia is attempting to bake it in from day one.

What’s on the Agenda

The programming leans into both big-picture strategy and hands-on execution—arguably the most in-demand combination in marketing right now.

Main Stage: “The Big Picture”
Expect macro-level discussions on how AI, data, and shifting consumer behavior are reshaping marketing across Asia.

Focused Tracks:

• Creating Customer Value: Data-driven engagement, personalization, and campaign performance

• Excellence in B2B: Rethinking B2B marketing strategies in a digital-first world

Knowledge Lounge
Smaller, informal sessions focused on practical tools and real-world case studies—less theory, more application.

C-Suite Boardrooms
Closed-door discussions for CMOs and strategy leaders, designed for candid peer exchange rather than polished presentations.

This mix mirrors a broader industry trend: marketers are no longer just storytellers—they’re operators, expected to connect brand, data, and revenue in measurable ways.

Why Kuala Lumpur—and Why Now

Choosing Kuala Lumpur as the launch city is a strategic play. The city has positioned itself as a regional hub with strong connectivity across Southeast Asia, making it accessible for marketers from Singapore, Indonesia, Thailand, and beyond.

Timing is just as important. Asia’s marketing landscape is evolving rapidly, driven by:

• Accelerated digital adoption

• Rising investment in MarTech and AI

• Increasing demand for measurable ROI

• A growing emphasis on first-party data strategies

In short, the region is primed for a platform that brings together brand marketers, tech leaders, and agencies in one room.

A Signal for the Events Industry

FoM Asia’s launch also says something about where marketing events are headed.

Instead of bigger expos and broader agendas, the emphasis is shifting toward:

• Curated audiences over mass attendance

• Actionable insights over inspiration alone

• Peer exchange over passive listening

It’s a model that competes less with trade shows and more with executive forums—where the value lies in who’s in the room as much as what’s on stage.

The Bottom Line

With FoM Asia, Haymarket is betting that Asia’s marketing leaders don’t need another conference—they need a focused, high-impact environment that respects their time and delivers tangible value.

If it works, expect more global event brands to follow suit, trading scale for substance in a region that’s quickly becoming central to the future of marketing.

Get in touch with our MarTech Experts.

When CEOs talk about AI, the ambition is rarely the problem—execution is. A new joint venture between Teneo and Thoughtworks aims to close that gap, promising to turn boardroom strategy into production-ready AI systems in a matter of months.

Announced today, the partnership blends Teneo’s high-level advisory reach with Thoughtworks’ deep engineering bench—more than 10,000 technologists across design, product engineering, and AI. The pitch is straightforward: help enterprises move from AI ambition to measurable business outcomes at a pace that matches today’s market volatility.

It’s a bold claim in a space crowded with transformation consultancies, but the firms are betting that tighter integration between strategy and execution—rather than treating them as separate phases—will resonate with CEOs under pressure to deliver results.

From AI Vision to Production in 90 Days

The standout hook here is speed. According to the companies, the venture is structured around aggressive timelines:

• Align on new product concepts in three days

• Build a working prototype in three weeks

• Deploy production systems in three months

That’s a sharp contrast to traditional enterprise transformation cycles, which often stretch into multi-year roadmaps with unclear ROI.

Thoughtworks CEO Mike Sutcliff framed the issue bluntly: AI initiatives fail when strategy, culture, and execution move at different speeds. This venture attempts to synchronize all three from day one—pairing executive advisors with engineers and data scientists in unified teams.

In practical terms, that means fewer slide decks and more shipped software.

Why This Matters Now

The timing isn’t accidental. Enterprises are pouring billions into AI infrastructure—often via hyperscalers like Amazon Web Services, Google, Microsoft, and hardware players like NVIDIA—but many are struggling to show tangible returns.

This has created a widening “AI execution gap”:

• Plenty of pilots, few scaled deployments

• Heavy investment, unclear ROI

• Fragmented ownership across business and IT

That’s the gap Teneo and Thoughtworks are targeting. By working directly with CEOs and executive teams, the venture positions itself above typical IT consulting engagements—closer to strategic decision-making, but with the ability to actually build and deploy systems.

It’s also a signal of how the consulting market is evolving. Firms are increasingly moving toward hybrid models that combine advisory, product development, and AI delivery in one offering—something competitors like Accenture and McKinsey have been pushing aggressively.

What the Venture Will Actually Do

Rather than offering generic AI consulting, the joint venture is structured around specific CEO-level priorities. Its services span:

• Scaling enterprise AI programs, including generative AI and advanced analytics

• Modernizing operating models and core systems

• Improving productivity and financial resilience through digital tools

• Enhancing stakeholder engagement with AI-driven insights

• Managing geopolitical and market risk via real-time monitoring

• Transforming customer and employee experiences through modern platforms

Notably, the focus isn’t just on technology—it’s on aligning strategy, operations, and execution simultaneously. That’s a subtle but important shift from traditional consulting models, where strategy often precedes (and disconnects from) implementation.

A CEO-Centric Play

Teneo CEO Paul Keary’s comments highlight another trend: the CEO is increasingly becoming the de facto “AI leader” inside large organizations.

That reflects a broader shift in enterprise tech. AI is no longer confined to IT departments—it’s reshaping business models, risk strategies, and even corporate reputation. As a result, decisions about AI deployment are moving into the C-suite.

By positioning itself as a CEO advisory-led venture, Teneo and Thoughtworks are effectively targeting the highest level of enterprise decision-making—where budgets, priorities, and timelines are set.

Built for Global Scale

The venture will be headquartered in New York, with hubs across the Americas, Europe, the Middle East, and Asia-Pacific. It will also tap into Thoughtworks’ partner ecosystem, including players like Databricks and Mechanical Orchard, to accelerate delivery.

That global footprint matters. AI transformation isn’t just a technical challenge—it’s shaped by regional regulations, geopolitical risks, and market dynamics. The ability to operate across jurisdictions could be a differentiator, especially for multinational clients.

The Bigger Picture

This launch underscores a broader reality: AI transformation is entering a new phase. The hype cycle is giving way to execution pressure, and enterprises are being forced to prove that their investments can deliver real business value.

In that environment, firms that can bridge the gap between strategy and shipping code have an edge.

Whether Teneo and Thoughtworks can deliver on their ambitious timelines remains to be seen. But the premise—AI transformation measured in weeks, not years—is exactly what many enterprises are now demanding.

And if they’re right, the consulting playbook may be due for a rewrite.

Get in touch with our MarTech Experts.

AI messaging platform Tells.co has received approval to deploy RCS Business Messaging in the United States, allowing the company to run production campaigns using the next generation of mobile messaging technology.

The move places Tells among the early platforms in the U.S. capable of launching live RCS campaigns for businesses, a milestone that could reshape how brands interact with customers through messaging.

RCS—short for Rich Communication Services—is widely considered the most significant upgrade to business messaging since SMS. Unlike traditional text messages, RCS enables interactive and multimedia experiences directly inside a consumer’s default messaging app.

That means brands can now deliver high-resolution images, interactive product carousels, branded sender identities, and action buttons within a conversation thread—without requiring customers to download a dedicated mobile app.

Messaging’s Next Evolution

For years, SMS has remained one of the most reliable communication channels between businesses and customers. But its limitations—plain text messages and minimal interactivity—have increasingly stood out in a world dominated by mobile apps and rich media.

RCS aims to bridge that gap.

The technology allows businesses to transform basic text messages into interactive micro-experiences, where users can browse products, watch videos, schedule appointments, or complete transactions directly within the chat interface.

Momentum for RCS accelerated recently when Apple confirmed support for the protocol across its messaging ecosystem, joining long-standing adoption among Android devices and telecom carriers.

With both major mobile platforms now supporting the technology, RCS is rapidly gaining traction as a potential successor—or at least a powerful complement—to SMS marketing.

Tells.co’s Early Push Into RCS Campaigns

According to David Schlaegel, co-founder of Tells.co, the company designed its platform to support the future of messaging rather than relying solely on legacy communication channels.

“We built Tells to support where messaging is going, not where it's been,” Schlaegel said. “RCS allows businesses to deliver experiences that previously required dedicated mobile apps. Now those experiences can happen directly inside a text conversation.”

With its newly approved deployment capability, Tells clients can begin running RCS-based marketing and customer engagement campaigns in production environments.

This early access could prove important as adoption accelerates.

“Most businesses are still trying to understand what RCS is,” Schlaegel added. “Our clients are already using it in production campaigns. That early head start will matter as the channel scales.”

Rich Messaging Features Built for Engagement

Tells has already rolled out several advanced features designed to take advantage of RCS’s interactive capabilities.

Among them:

AI-Powered Personalized Video Messages
The platform can generate personalized video content using artificial intelligence and deliver it directly within an RCS conversation thread.

Interactive Product Carousels
Businesses can display swipeable product catalogs with embedded action buttons, allowing customers to browse offerings without leaving the messaging interface.

Verified Brand Profiles
RCS supports branded sender identities, enabling businesses to display verified logos and company names inside the conversation—helping reduce spam concerns and build trust.

Actionable Links and Buttons
Messages can include interactive options such as:

• Tap-to-call customer support

• Appointment scheduling

• Payment links

• Directions to physical locations

Together, these tools effectively transform text conversations into mini digital storefronts or service portals.

Why RCS Could Transform Business Messaging

While SMS remains a powerful marketing channel due to its high open rates, it has largely remained unchanged since the 1990s.

RCS introduces features that bring messaging closer to the capabilities typically found in mobile apps or social media platforms.

These include:

• Rich media content

• Interactive user interfaces

• Real-time engagement tools

• Verified brand identities

For businesses, this shift opens the door to app-like experiences delivered through messaging, reducing friction for customers who may not want to install additional apps.

It also aligns with a broader trend toward conversational commerce, where purchasing and service interactions increasingly occur inside chat environments.

A Competitive Messaging Landscape

RCS enters a competitive messaging ecosystem that already includes major business communication channels such as:

• WhatsApp

• Facebook Messenger

• iMessage

However, unlike these platforms, RCS operates within a device’s native messaging app, potentially giving it broader reach without requiring users to sign up for new services.

That native integration could make RCS particularly attractive for brands seeking high engagement without additional app downloads.

Early Movers May Gain an Advantage

Although RCS adoption is still in its early stages in the United States, the technology’s recent support across major mobile ecosystems suggests it could soon become a mainstream marketing channel.

Companies that experiment early may gain valuable experience in designing interactive messaging campaigns before competitors catch up.

For platforms like Tells.co, securing approval to deploy production campaigns now could position them as key infrastructure providers for businesses exploring the future of mobile engagement.

If RCS adoption continues to accelerate, the humble text message may soon evolve into one of the most sophisticated communication tools in digital marketing.

Get in touch with our MarTech Experts.