Oracle NetSuite is expanding its artificial intelligence strategy with new capabilities designed to help businesses integrate the AI models and assistants of their choice directly into enterprise workflows. The company announced several enhancements to its NetSuite AI Connector Service, introducing tools that allow organizations to securely connect external AI platforms to NetSuite data while maintaining governance over how those models access finance, operations, and analytics information.

The update includes the launch of NetSuite AI Connector Service Companion, support for Model Context Protocol (MCP) Apps, and deeper integration with NetSuite Analytics Warehouse. Together, these additions aim to help enterprise teams apply AI across finance, reporting, and operational analysis without requiring complex integration work or advanced prompt engineering expertise.

Enterprise software providers are racing to embed generative AI capabilities into business applications. But many organizations are already experimenting with multiple AI assistants—from enterprise copilots to custom models—creating a new integration challenge: how to connect these tools to operational data safely.

With its latest announcement, Oracle is positioning NetSuite as a flexible foundation for that emerging AI ecosystem.

Rather than forcing customers to rely on a single proprietary AI model, NetSuite’s strategy focuses on letting companies connect their preferred AI systems to ERP data, while controlling permissions and governance through the ERP platform.

“Many customers are already working with AI assistants,” said Evan Goldberg, founder and executive vice president at Oracle NetSuite. “These extensions make it easier to securely connect their own AI to their data and workflows.”

The approach reflects a broader shift across enterprise software markets, where vendors increasingly support open AI architectures instead of tightly locked ecosystems.

Bringing External AI Into ERP Workflows

At the center of the announcement is NetSuite AI Connector Service, a standards-based integration framework designed to link AI models with ERP data.

The service supports the Model Context Protocol (MCP), an emerging framework that enables AI systems to interact with enterprise software while respecting application permissions and workflows.

In practical terms, this means companies can connect AI assistants—whether developed internally or through third-party platforms—to NetSuite while controlling:

• what data the AI can access
• which workflows it can trigger
• how outputs are governed and audited

This capability is becoming increasingly important as generative AI expands into finance operations, marketing analytics, and forecasting workflows.

Research from Gartner estimates that over 80% of enterprises will use generative AI APIs or models in production applications by 2026, up from less than 5% in 2023. That surge is pushing ERP vendors to rethink how AI integrates with core business systems.

AI Connector Service Companion: A Finance-Focused AI Layer

One of the most significant additions is the NetSuite AI Connector Service Companion, which aims to make AI assistants more reliable when interacting with financial systems.

Finance workflows require strict accuracy, permissions, and auditability—areas where general-purpose AI models often struggle.

The Companion tool addresses this challenge by providing a structured layer of prompts, context, and governance aligned with NetSuite data models.

Among its key features:

A finance-specific prompt library

The system includes more than 100 curated prompt templates designed for finance and operational use cases. These templates reflect NetSuite’s internal data structures, terminology, and permissions.

Users can modify the prompts or create their own variations to match internal workflows.

Reusable AI “skills”

The platform introduces reusable instruction sets that guide AI models when interacting with NetSuite data. These skills help convert generic AI assistants into NetSuite-aware agents capable of performing specialized finance tasks.

Role-based governance

Preconfigured role templates align AI access with specific enterprise roles such as:

• CFO
• Controller
• Accounts Receivable Analyst
• Accounts Payable Analyst
• Treasury Analyst

This structure ensures AI interactions remain consistent with enterprise security policies.

MCP Apps Bring NetSuite Interfaces Into AI Assistants

Another major component of the update is NetSuite MCP Apps, which introduces structured interfaces inside AI assistants.

Instead of relying solely on free-form text prompts, MCP Apps allow users to interact with NetSuite through visual components embedded within AI tools.

Examples include:

• Prompt Library access
• Report selection tools
• Record pickers for NetSuite data

These structured interfaces reduce the trial-and-error often associated with generative AI prompts.

For enterprise teams, the benefit is efficiency: users can navigate financial reports, select records, and configure queries through familiar NetSuite-style menus.

This approach mirrors broader trends in enterprise AI design. Many platforms are moving toward guided AI interactions, combining conversational interfaces with structured UI elements.

Companies like Microsoft, Salesforce, and Adobe are also building similar hybrid interfaces that blend generative AI with traditional application workflows.

Expanding AI Analytics Through NetSuite Analytics Warehouse

The final component of the announcement focuses on analytics.

The NetSuite AI Connector Service for NetSuite Analytics Warehouse extends AI access beyond transactional ERP data.

With this capability, AI systems can analyze:

• historical operational data
• aggregated analytics datasets
• third-party business data integrated into the warehouse

The result is a broader analytical view that enables AI-driven forecasting and cross-system insights.

According to research from IDC, global spending on AI-enabled analytics platforms is expected to surpass $300 billion by 2027, as enterprises adopt AI-driven decision support systems.

For NetSuite customers, extending AI into the analytics warehouse opens the door to use cases such as:

• financial forecasting
• supply chain trend analysis
• marketing performance modeling
• cross-system operational insights

Why the Announcement Matters for Enterprise Marketing and Finance Teams

ERP platforms sit at the center of enterprise data infrastructure.

That makes them an increasingly important integration point for AI systems used by marketing, finance, and operations teams.

For marketing leaders in particular, access to ERP-level data can unlock deeper insights into revenue performance and customer lifetime value.

Platforms like NetSuite often connect with broader marketing ecosystems that include tools from Google, CRM platforms from Salesforce, and marketing experience systems from Adobe.

By enabling external AI assistants to interact with ERP data, NetSuite effectively turns the ERP platform into an AI data backbone for enterprise operations.

The flexibility to integrate multiple AI systems may also appeal to organizations experimenting with different generative AI tools across departments.

A Competitive Shift Toward Open AI Ecosystems

NetSuite’s strategy highlights a growing competitive dynamic in enterprise software: AI openness versus AI lock-in.

Many vendors are building tightly integrated AI copilots tied to their own platforms. Others are embracing more open architectures that allow enterprises to plug in external AI models.

NetSuite’s AI Connector Service leans toward the latter approach.

Instead of replacing existing AI assistants, the platform acts as a secure gateway between ERP data and AI tools.

That flexibility could become increasingly valuable as organizations deploy AI systems across marketing automation, finance analytics, and operational planning.

Market Landscape

The ERP market is undergoing a significant transformation as AI capabilities become embedded into enterprise systems.

Research from Statista suggests the global ERP software market could exceed $110 billion by 2030, driven by cloud adoption and AI-powered automation.

At the same time, enterprise leaders are demanding platforms that integrate with broader AI ecosystems rather than forcing them into a single vendor’s AI stack.

NetSuite’s AI Connector Service enhancements reflect that demand.

By allowing companies to bring their own AI models while maintaining governance through ERP permissions and workflows, the platform positions itself as a central AI integration layer for enterprise operations.

Top Insights

• Oracle NetSuite introduced new capabilities in its AI Connector Service that allow enterprises to integrate external AI assistants with ERP workflows while maintaining strict data governance and role-based access controls.
• The NetSuite AI Connector Service Companion introduces finance-specific prompts and reusable AI skills, helping general-purpose AI models interact reliably with ERP financial data and operational workflows.
• New MCP Apps embed NetSuite interfaces directly inside AI assistants, allowing users to navigate reports, records, and data structures through structured menus instead of complex prompt engineering.
• Expanded integration with NetSuite Analytics Warehouse enables AI systems to analyze historical, transactional, and third-party datasets, opening new use cases for forecasting and cross-system analytics.
• The announcement reflects a broader enterprise trend toward open AI ecosystems where companies connect multiple AI tools to core business platforms rather than relying on single-vendor AI solutions.

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AI-powered advertising platform StackAdapt has been recognized as a Strong Performer in The Forrester Wave™: Omnichannel Advertising Platforms, Q1 2026, an industry evaluation conducted by Forrester.

The report assessed leading omnichannel advertising platforms based on a range of criteria, including current capabilities, strategic vision, and customer feedback.

StackAdapt achieved the highest possible scores in several categories, including self-service capabilities, onboarding and training support, and pricing transparency.

Forrester Evaluation Highlights Platform Strengths

The The Forrester Wave™: Omnichannel Advertising Platforms, Q1 2026 evaluated vendors across two primary dimensions: current offering and long-term strategy.

In addition to strong performance scores, StackAdapt received above-average feedback from customers participating in the evaluation.

According to the report, users praised the platform for its usability, cost-effectiveness, and responsive customer support.

The evaluation also marked StackAdapt’s participation in the first edition of Forrester’s Wave report focused specifically on omnichannel advertising platforms.

For the company, the recognition reflects its growing presence in the rapidly evolving adtech landscape.

AI-Driven Platform Supports Omnichannel Campaigns

The platform from StackAdapt enables marketers to manage advertising campaigns across multiple digital channels through a unified interface.

These channels include:

• connected TV (CTV)
• native advertising
• display advertising
• video advertising
• digital audio
• in-game advertising
• digital out-of-home (DOOH)

By consolidating campaign planning, activation, and optimization into a single environment, the platform aims to eliminate the fragmented workflows commonly associated with legacy advertising systems.

AI and automation capabilities within the platform analyze campaign performance data and help marketers optimize targeting, bidding strategies, and creative delivery.

Bridging MarTech and AdTech

According to Forrester, advertisers increasingly seek comprehensive platforms that reduce operational complexity while providing advanced capabilities.

The report notes that modern advertisers want solutions capable of supporting multiple forms of artificial intelligence—including predictive, generative, and agentic AI—within unified advertising workflows.

This shift reflects the broader convergence of marketing technology and advertising technology (AdTech).

Platforms that integrate audience intelligence, campaign orchestration, and cross-channel optimization are becoming central components of digital marketing infrastructure.

Executives at StackAdapt say the company’s vision aligns with this trend by helping marketers understand audiences more effectively while simplifying campaign management.

Expanding Capabilities for Global Advertising

Over the past year, StackAdapt has continued to expand its platform capabilities.

Recent developments include tools designed to help brands and agencies:

• consolidate media buying workflows
• streamline omnichannel campaign execution
• improve campaign performance through AI insights
• access premium global advertising inventory

These enhancements aim to support enterprise-scale advertising strategies while maintaining ease of use for marketers.

Industry Recognition Reflects Platform Momentum

Recognition in The Forrester Wave™: Omnichannel Advertising Platforms, Q1 2026 places StackAdapt among leading vendors in the omnichannel advertising market.

Industry analysts note that demand for integrated advertising platforms continues to grow as brands seek more efficient ways to manage campaigns across increasingly complex digital ecosystems.

By combining AI-driven automation, cross-channel campaign management, and strong customer support, the platform aims to help marketers deliver measurable outcomes while reducing operational complexity.

Key Insights

• StackAdapt was named a Strong Performer in The Forrester Wave™: Omnichannel Advertising Platforms, Q1 2026.
• The company received top scores for self-service capabilities, onboarding and training, and pricing transparency.
• The platform supports campaigns across CTV, native, display, video, audio, in-game, and DOOH channels.
• AI-driven automation helps marketers optimize campaigns and improve performance across channels.
• The recognition reflects growing demand for integrated omnichannel advertising platforms.

Get in touch with our MarTech Experts.

Enterprise video platform provider Kaltura has announced a strategic partnership with Descript to deliver integrated AI-powered video creation and editing capabilities for organizations across multiple industries.

The collaboration combines Kaltura’s AI-driven video production tools and avatar technology with Descript’s script-based video editing platform. Together, the companies aim to help enterprises scale video content production while maintaining governance, accuracy, and compliance—particularly in highly regulated sectors such as healthcare.

The partnership has already resulted in a commercial deployment at a major medical center, where the integrated solution is being used to produce training and communication content across departments.

Growing Enterprise Demand for AI Video Workflows

Organizations worldwide are increasingly adopting AI-powered video tools to improve internal communications, employee training, and customer engagement.

Video has become a critical medium for enterprise knowledge sharing, but traditional production workflows can be time-consuming and resource-intensive.

By integrating AI-powered creation and editing tools, the partnership between Kaltura and Descript aims to simplify the process of producing professional-grade content.

Enterprises can use the combined platform to automate repetitive production tasks while ensuring subject-matter experts retain control over messaging and content accuracy.

This approach allows organizations to increase production speed without sacrificing governance or oversight.

AI Avatars and Script-Based Editing Streamline Production

The integrated platform brings together two complementary capabilities.

Kaltura provides AI-powered video creation tools and digital avatars that can automatically generate professional video presentations from scripts or structured inputs.

Meanwhile, Descript offers a unique editing interface that allows users to edit video by editing text—making video production accessible even for non-technical teams.

Together, these capabilities enable enterprise teams to:

• produce video content faster
• edit and refine messaging using text-based workflows
• generate AI-driven visual presentations
• distribute content through enterprise video platforms

This integration allows organizations to manage the entire video lifecycle—from production and editing to publishing and distribution—within a unified workflow.

Healthcare Deployment Demonstrates Compliance Capabilities

One of the first joint implementations of the solution is taking place within a major healthcare organization.

Healthcare institutions often face strict compliance requirements regarding training materials, patient communications, and internal documentation.

The integrated platform enables healthcare teams to scale video production across departments while maintaining the governance standards required in regulated environments.

For the medical center deploying the technology, ease of use and human oversight were essential criteria.

By combining automated production tools with human review processes, the system allows experts to maintain control over messaging while leveraging AI to streamline technical production steps.

Supporting the Future of Enterprise Video

Executives from both companies say the partnership reflects broader enterprise demand for integrated AI solutions.

Lior Bukshpan, Head of Strategic Partnerships at Kaltura, described the collaboration as part of a broader shift toward practical AI adoption in enterprise environments.

Organizations increasingly want AI tools that improve productivity without adding complexity to existing workflows.

At the same time, enterprises are facing rising operational pressures, including cost management, workforce burnout, and the need to accelerate digital transformation initiatives.

Integrated AI platforms that simplify content production while maintaining compliance and oversight are becoming essential infrastructure for modern enterprises.

AI Video Platforms Expand Enterprise Content Capabilities

The partnership between Kaltura and Descript reflects a broader transformation in enterprise content creation.

As organizations increase their reliance on video for communication and training, AI-powered platforms are helping scale production in ways that were previously impractical.

By automating technical production tasks and integrating intuitive editing tools, enterprises can produce high-quality content faster and more efficiently.

For industries operating under strict regulatory oversight—such as healthcare, finance, and government—these technologies must also support strong governance frameworks.

The combined capabilities of Kaltura and Descript aim to meet both needs: rapid content production and enterprise-grade compliance.

Key Insights

• Kaltura and Descript formed a strategic partnership to deliver AI-powered enterprise video production tools.
• The integration combines AI video creation, avatars, and script-based editing workflows.
• A major healthcare organization has already adopted the solution for regulated video content production.
• The platform helps enterprises scale video creation for training, communications, and customer engagement.
• AI automation accelerates production while maintaining human oversight and governance. 

Get in touch with our MarTech Experts.

Brazilian pay-TV provider Mileto Tecnologia has selected the Synamedia Go platform from Synamedia to support its expanding over-the-top (OTT) streaming strategy.

The move positions Synamedia Go as the foundation for Mileto’s next-generation streaming service, enabling the company to deliver personalized viewing experiences powered by AI-driven content discovery and recommendations.

The deployment is part of a broader expansion strategy for Mileto as it strengthens its position in Brazil’s rapidly evolving digital media landscape.

OTT Expansion Drives Strategic Investments

The partnership follows several strategic initiatives undertaken by Mileto Tecnologia to expand its video distribution ecosystem.

Recent moves include:

• the acquisition of OiTV, a major direct-to-home (DTH) television provider
• a satellite distribution agreement with SES
• the launch of a new customer service portal aimed at improving subscriber engagement

Together, these initiatives reflect Mileto’s ambition to become a major digital video provider across Brazil.

Synamedia Go Powers Cloud-Native Streaming Platform

The Synamedia Go platform is built as an open, modular software-as-a-service (SaaS) OTT solution.

Developed by Synamedia, the system operates on a multi-tenant microservices architecture running on cloud-native infrastructure.

This design allows streaming providers to scale services rapidly while maintaining flexibility in how content is delivered and monetized.

The platform also supports advanced content aggregation capabilities that enable personalized viewing experiences.

For media companies and internet service providers, these features create new opportunities to bundle content, launch branded streaming services, and introduce additional monetization models.

AI-Powered Personalization Enhances Viewer Experience

A key component of the new platform is its use of artificial intelligence to improve content discovery.

AI-powered recommendation engines analyze viewer behavior to deliver personalized suggestions, helping audiences find relevant programming more quickly.

This functionality has become a major differentiator in modern streaming platforms, as media companies compete to improve engagement and reduce subscriber churn.

For Mileto Tecnologia, which holds extensive content rights in Brazil, the technology allows the company to maximize the value of its programming library.

Secure Streaming Infrastructure with VideoGuard

In addition to deploying Synamedia Go, Mileto will implement VideoGuard, a security platform designed to protect pay-TV content.

The conditional access system ensures that direct-to-home (DTH) satellite television services are accessed only by authorized users.

Content protection remains a critical component of streaming infrastructure as piracy and unauthorized access continue to challenge media providers worldwide.

By combining advanced security with scalable streaming technology, the partnership aims to deliver both reliability and protection across Mileto’s digital media ecosystem.

Expanding Streaming Across Brazil

Executives from both companies emphasized that the collaboration aligns technological innovation with ambitious growth plans.

Pedro Pedras, CEO of Mileto Tecnologia, said the platform will help the company enhance and differentiate its OTT services while expanding monetization opportunities.

Mileto’s leadership believes the platform will enable the company to evolve into a central hub for digital content distribution across Brazil.

Renato Svirsky, founder and director of Mileto, highlighted the importance of secure and scalable streaming technology as the company continues expanding its subscriber base.

Meanwhile, executives at Synamedia noted that the partnership combines Mileto’s market vision with the technical infrastructure required to support large-scale video delivery.

Streaming Platforms Drive Media Transformation

The collaboration reflects broader trends reshaping the global media industry.

Traditional pay-TV operators are increasingly investing in OTT platforms as audiences shift toward on-demand streaming services.

Cloud-based infrastructure, AI-driven personalization, and scalable content delivery systems are becoming essential components of modern video platforms.

By integrating these technologies into its digital strategy, Mileto Tecnologia aims to strengthen its position in Brazil’s competitive streaming market.

As media consumption continues evolving, partnerships between technology providers and media companies are expected to play a central role in shaping the future of digital entertainment.

Key Insights

• Mileto Tecnologia selected Synamedia Go to power its next-generation OTT streaming platform.
• The platform uses cloud-native microservices architecture to support scalable streaming services.
• AI-powered content discovery and recommendations will enhance viewer personalization.
• Mileto is also deploying VideoGuard to secure its DTH pay-TV services.
• The partnership supports Mileto’s broader expansion strategy in Brazil’s growing streaming market.

Get in touch with our MarTech Experts.

Global digital AI infrastructure provider Tata Communications has introduced IZO™ Data Centre Dynamic Connectivity, a software-defined networking platform designed to improve resilience and performance for enterprise data centre connectivity in an increasingly AI-driven world.

The platform introduces a self-healing network architecture that automatically detects disruptions and reroutes traffic in seconds, helping enterprises maintain uninterrupted data flows across global infrastructure.

As enterprises expand digital operations across cloud platforms, global data centres, and AI workloads, the need for reliable and scalable connectivity has become a critical business requirement.

Data Centre Connectivity Becomes Mission-Critical

Modern enterprises rely heavily on seamless connectivity between data centres to support operations ranging from financial transactions and manufacturing systems to streaming services and e-commerce platforms.

When those connections fail, the consequences can be immediate and costly.

Traditional data centre-to-data centre (DC-to-DC) networks were originally designed for predictable traffic patterns and centralized infrastructure. However, today’s digital environment is far more complex.

Organizations now operate across multiple clouds, regions, and digital ecosystems, moving massive volumes of real-time data to power applications, analytics platforms, and artificial intelligence workloads.

This shift has placed new demands on global Business infrastructure.

Self-Healing Architecture Designed for AI-Driven Infrastructure

The new platform from Tata Communications aims to address these evolving requirements with a resilient, automated networking model.

IZO™ Data Centre Dynamic Connectivity introduces deterministic multi-path routing, allowing data traffic to move across multiple optimized routes simultaneously.

If a disruption occurs—such as cable damage, route failure, or sudden spikes in demand—the network automatically redirects traffic through alternate paths without manual intervention.

According to the company, the system can deliver more than 99.99% service availability across mission-critical infrastructure.

This capability is particularly important as geopolitical tensions, infrastructure outages, and global bandwidth demand increasingly affect digital operations.

Global Data Centre Coverage Across Five Continents

The platform connects major enterprise data centres across five continents, providing organizations with a unified network environment for global operations.

Instead of relying on static connectivity links, enterprises can dynamically adjust network capacity based on real-time demand.

Through a digital interface and API integrations, IT teams can:

• monitor connectivity performance in real time
• receive proactive alerts about potential disruptions
• scale bandwidth as workloads change
• add network routes when required

This level of operational visibility allows organizations to manage connectivity as a dynamic resource rather than a fixed infrastructure investment.

Predictive Intelligence and AI-Driven Insights

In addition to automation, the platform integrates predictive analytics to help enterprises anticipate network requirements.

AI-driven insights allow organizations to forecast future capacity needs based on workload patterns and data traffic trends.

This capability helps enterprises avoid both under-provisioning and over-provisioning network resources.

If a sudden surge in demand occurs—for example, due to increased AI processing workloads or large-scale data transfers—network capacity can be expanded instantly through a self-service interface.

Such flexibility is increasingly important as enterprises deploy AI-powered applications that require high-performance, low-latency data flows between distributed computing environments.

Flexible Consumption Model Reduces Infrastructure Costs

The new networking model also introduces a consumption-based pricing structure.

Instead of maintaining large amounts of unused backup capacity, organizations can activate additional resilience and bandwidth only when necessary.

According to Tata Communications, this approach can help enterprises reduce operational costs by up to 30% while still maintaining high levels of network reliability.

By aligning infrastructure spending with real-time demand, companies can shift from reactive crisis management toward strategic digital growth.

Supporting the Global Digital Economy

Data centre connectivity has become a foundational component of the modern digital economy.

Industries including finance, IT services, manufacturing, retail, and streaming platforms rely on high-availability infrastructure to ensure continuous service delivery.

Genius Wong, Executive Vice President for Core and Next-Generation Connectivity Services and Chief Technology Officer at Tata Communications, said the new platform reflects a broader shift toward autonomous network operations.

Rather than responding to outages after they occur, networks are increasingly designed to anticipate disruptions and adapt automatically.

This approach transforms resilience from an emergency response mechanism into a built-in capability of the infrastructure itself.

As global enterprises continue expanding AI adoption and multi-cloud architectures, networking platforms capable of delivering automated resilience and predictive intelligence may play a central role in supporting future digital ecosystems.

Key Insights

• Tata Communications launched IZO™ Data Centre Dynamic Connectivity to improve global data centre resilience.
• The platform introduces self-healing networking with deterministic multi-path routing.
• Enterprises can achieve >99.99% service availability with automated traffic rerouting.
• AI-driven predictive analytics help organizations forecast bandwidth requirements.
• A consumption-based pricing model can reduce operational costs by up to 30%.

Get in touch with our MarTech Experts.

Headless CMS provider Storyblok has introduced FlowMotion, a new automation and orchestration layer designed to transform content updates into automated workflows across marketing systems, developer environments, and AI-powered tools.

The platform aims to address a growing operational challenge for modern digital teams: content changes rarely stop at publishing. A single update can trigger approvals, localization workflows, catalog changes, search re-indexing, and distribution across multiple channels and regions.

FlowMotion enables teams to connect these events into structured workflows, replacing manual coordination that often occurs through messaging tools, spreadsheets, and custom scripts.

As organizations accelerate content production and expand global digital experiences, the need for coordinated workflow automation has become increasingly critical.

Content Operations Still Depend on Manual Coordination

New research conducted by Storyblok among 200 marketers working with global brands highlights how fragmented content workflows remain across organizations.

The survey found that 75% of marketers spend more than six hours per week coordinating content work, including approvals, follow-ups, and routing updates between systems.

Additionally:

• 71% said their tools do not communicate effectively with one another
• 90% reported lacking end-to-end workflow coordination
• 50% said content updates frequently go live late, incomplete, or inconsistent across regions

These challenges often emerge in large digital ecosystems where marketing, development, product, and operations teams rely on multiple platforms to manage websites, e-commerce, mobile apps, and customer engagement channels.

Manual coordination between these systems slows execution and increases the risk of errors.

Developers Also Face Workflow Complexity

Developers experience similar inefficiencies when implementing automation within content operations.

A parallel survey of 200 developers working with global brands revealed that 88% said implementing new automation workflows takes more than a week, while 37% reported the process can take more than a month.

Maintaining workflow infrastructure also consumes engineering resources.

According to the research:

• 78% of development teams spend more than 10% of engineering time maintaining integrations, scripts, and workflow logic
• Only 8% of organizations currently have centralized and observable workflow orchestration

These findings suggest that both marketing and engineering teams struggle with fragmented workflow systems.

FlowMotion Connects Content Events to Automated Workflows

FlowMotion is designed to bridge these gaps by linking content events inside the Storyblok platform to automated, event-driven workflows.

Actions such as content creation, updates, approvals, translations, scheduling, and publishing can trigger automated sequences across connected tools.

The platform is built on a fully managed, single-tenant instance of n8n, which provides access to more than 500 integrations.

Through these integrations, workflows can perform multiple tasks automatically, including:

• triggering approval processes
• synchronizing CRM and sales platforms
• updating product catalogs
• rolling out content across markets
• re-indexing search systems
• coordinating localization workflows

Teams can also pause workflows for human approvals, enforce governance policies, and ensure actions occur only where relevant.

Enterprise Governance and Observability

FlowMotion includes enterprise-level governance features designed to help organizations manage complex digital operations.

Workflows are versioned, observable, and debuggable, with built-in audit trails that allow teams to track what actions occurred and when.

This capability helps organizations meet governance requirements and maintain visibility across distributed teams and systems.

Examples of automated use cases include:

• triggering legal reviews for pricing changes in regulated regions
• rolling out storefront updates gradually across markets
• synchronizing customer relationship management systems after approvals
• updating support documentation when FAQs change

Such orchestration ensures that content updates propagate consistently across digital environments.

AI Capabilities Integrated Into Workflow Automation

FlowMotion also incorporates artificial intelligence into content workflows.

Organizations can run AI enrichment, tagging, summarization, and routing as part of automated processes.

Importantly, AI tasks can be executed using a company’s own API keys, allowing teams to control where and how AI services operate.

This governance layer is particularly important as AI becomes more deeply embedded in content production pipelines.

According to Storyblok’s research, 84% of marketers believe stronger governance frameworks would increase trust in AI-powered content workflows.

A Step Toward Autonomous Content Operations

For many organizations, content management systems are evolving from publishing tools into orchestration hubs for digital experiences.

Dominik Angerer, CEO and co-founder of Storyblok, said FlowMotion aims to centralize workflow logic that is often scattered across scripts, webhooks, and individual tools.

With visual workflow design capabilities, teams can map processes directly inside the platform while still extending functionality with custom code when necessary.

The system also supports triggers through machine communication protocols, enabling automated systems and AI agents to participate in workflow orchestration.

Industry analysts say this shift reflects broader trends in enterprise content infrastructure, where automation, AI integration, and cross-system coordination are becoming essential capabilities.

As organizations scale digital operations across websites, apps, commerce platforms, and AI-driven experiences, workflow orchestration tools like FlowMotion may play a key role in enabling faster and more reliable content delivery.

Key Insights

• Storyblok launched FlowMotion to automate content workflows across marketing, development, and AI systems.
• Surveys show 75% of marketers spend more than six hours weekly coordinating content updates manually.
• 88% of developers say building automation workflows takes more than a week, highlighting integration complexity.
• FlowMotion connects CMS events to automated workflows using n8n with 500+ integrations.
• The platform includes governance features, audit trails, and AI workflow integration to support enterprise-scale content operations. 

Get in touch with our MarTech Experts.

Global B2B companies remain optimistic about growth, yet many are struggling to translate ambition into results. A new industry survey suggests the gap between expectations and actual performance is widening as companies grapple with artificial intelligence adoption challenges and rising geopolitical uncertainty.

Research from Bain & Company shows that a growing share of companies are failing to meet revenue targets despite strong confidence among leadership teams. The firm’s 2026 B2B Growth Agenda report, based on responses from more than 1,100 senior executives across 18 industries worldwide, highlights how technological disruption and volatile economic conditions are reshaping commercial strategy.

The findings reveal a striking contradiction: while 91% of executives believe they will achieve their 2026 growth goals, a growing number missed targets the year before.

In 2025, 42% of companies failed to reach revenue goals, up sharply from 32% in 2024, even though the majority of leaders had expected to succeed.

The results illustrate how quickly market conditions—and the technology shaping them—are evolving.

Confidence Remains High Despite Recent Missed Targets

The survey results show that executive optimism remains strong despite recent setbacks.

Nearly nine out of ten leaders expected their companies to hit growth targets in 2025. Yet the percentage of companies falling short rose significantly compared with the previous year.

According to Bain, companies are projecting 20% higher revenue growth expectations for 2026 compared with last year. Still, the growing gap between expectations and outcomes suggests many organizations may be underestimating the operational changes required to succeed in increasingly dynamic markets.

Industry analysts point to several factors driving the disconnect, including rapid technological change, macroeconomic uncertainty, and shifting buyer behavior in B2B markets.

Jamie Cleghorn, global head of Bain’s customer practice, described volatility as a permanent condition rather than a temporary disruption.

Executives, he said, are often setting aggressive growth targets while relying on commercial operating models that were designed for slower-moving markets.

As technology innovation accelerates and competitive landscapes evolve, companies are finding that traditional sales and marketing systems struggle to adapt quickly enough.

Artificial Intelligence Becomes a Growth Imperative

Artificial intelligence has become one of the most prominent themes in corporate growth strategies.

According to Bain’s research, 90% of surveyed companies are experimenting with AI technologies across functions such as marketing, sales, operations, and customer service.

Yet the results remain inconsistent.

Nearly 60% of executives say their organizations lack the data infrastructure or technology foundation necessary to scale AI effectively.

Without those capabilities, many AI initiatives remain experimental rather than operational.

Leading companies, however, appear to be approaching AI adoption differently.

Instead of deploying isolated use cases, high-performing organizations are redesigning their commercial processes end to end. AI is embedded directly into workflows—from lead generation and demand forecasting to pricing strategies and sales operations.

These organizations report twice the AI-driven revenue growth and roughly 1.8 times higher cost efficiency compared with peers.

The difference, according to Bain researchers, lies in operational integration rather than experimentation.

Companies that treat AI as a core infrastructure capability—not a standalone tool—are better positioned to translate technology investments into measurable business outcomes.

Legacy Workflows Remain a Barrier to AI Adoption

One of the most persistent obstacles to AI adoption is the complexity of legacy business processes.

Many B2B organizations still rely on fragmented systems, manual workflows, and inconsistent data environments.

These operational limitations make it difficult to deploy AI tools that require structured data and standardized processes.

Rob Stein, a partner in Bain’s Customer Strategy and Marketing practice, said companies must first simplify and standardize commercial operations before AI can deliver meaningful impact.

Without that foundation, automation and machine learning technologies struggle to scale.

In practical terms, this means organizations must rethink how their go-to-market teams operate.

Processes such as lead qualification, sales pipeline management, pricing decisions, and customer engagement workflows often require modernization before AI systems can enhance them.

Companies that successfully combine process redesign, targeted AI use cases, and structured change management programs tend to capture the most value from AI initiatives.

A Surprising Weakness: Differentiation

Perhaps the most striking finding in Bain’s research involves competitive positioning.

Despite intense competition across nearly every industry, very few companies believe they have a clearly defined value proposition.

Only 4% of executives surveyed said their organization has a strong, consistently understood value proposition.

For many companies, the challenge lies in articulating how their products or services are meaningfully different from competitors.

Nearly half of respondents cited product or service differentiation as the biggest barrier to growth.

The performance impact of differentiation appears significant.

Companies with a clear value proposition achieved 19% revenue growth in 2025, compared with 12% for those without one.

The findings suggest that strategic messaging—how companies communicate their value to customers—remains a critical driver of growth.

Brand perception also plays an increasingly important role in B2B markets.

Nearly 40% of revenue and margin leaders said brand reputation is a major factor in winning and expanding customer relationships.

That trend highlights the growing importance of demand generation, brand marketing, and early-stage buyer engagement.

Industry Impacts Vary Across Sectors

The challenges facing B2B companies are not uniform across industries.

Bain’s research indicates that different sectors are responding to volatility in distinct ways.

In healthcare and life sciences, companies are dealing with persistent pricing pressures and regulatory constraints. Organizations in these sectors are focusing on operational efficiency and innovation to maintain margins.

Technology, media, and telecommunications companies face a different challenge: intense competition and rapidly evolving customer expectations. These organizations are prioritizing customer acquisition and retention strategies while investing heavily in AI and digital platforms.

Meanwhile, financial institutions—including banks—are emphasizing sales productivity and modernization of go-to-market technologies to remain competitive in uncertain economic conditions.

Industrial sectors such as advanced manufacturing, aerospace, logistics, and building products are also experiencing growing operational complexity.

Global supply chains, geopolitical risks, and fluctuating demand patterns are forcing companies in these industries to rethink commercial planning and execution.

The Bigger Picture: A New Commercial Playbook Emerges

The findings from Bain’s research reflect a broader shift in how companies approach growth.

Traditional sales and marketing strategies were designed for relatively stable markets. Today’s environment, however, is defined by rapid technological change, geopolitical uncertainty, and increasingly sophisticated buyers.

To adapt, organizations must develop more flexible commercial operating models.

These models rely heavily on data analytics, AI-driven insights, and agile decision-making frameworks.

Industry analysts at Gartner and Forrester have similarly noted that B2B organizations are investing heavily in advanced analytics and AI-enabled revenue platforms.

The goal is to create systems capable of translating real-time market signals into actionable strategies.

Companies that succeed in this AI transformation often focus on three priorities:

• modernizing commercial technology stacks
• embedding AI into everyday decision-making
• strengthening brand differentiation and customer engagement

Together, these capabilities allow organizations to respond more quickly to changing market conditions.

As Bain’s research suggests, companies that combine strategic clarity with operational agility are more likely to outperform peers in volatile environments.

Top Insights

• Bain & Company’s 2026 B2B Growth Agenda report finds 42% of companies missed revenue targets in 2025, highlighting a widening gap between executive growth ambitions and market realities.

• While 90% of organizations are experimenting with AI, nearly 60% lack the data infrastructure and technology foundations needed to scale AI effectively across operations.

• Companies embedding AI directly into commercial workflows report twice the AI-driven revenue growth and 1.8 times greater cost efficiency than peers.

• Only 4% of surveyed executives say their organization has a clearly defined value proposition, a factor strongly correlated with faster revenue growth.

• Growing geopolitical uncertainty and technology disruption are forcing companies across industries to rethink traditional commercial strategies.

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Financial planning and analysis (FP&A) teams have long relied on spreadsheets, disconnected reporting tools, and manual workflows to translate financial data into insights. For many mid-market organizations, that process often requires exporting planning data into separate business intelligence systems before executives can visualize performance metrics.

Centage is attempting to close that gap with a major upgrade to its analytics capabilities. The company announced enhanced dashboard functionality within its FP&A platform, positioning the release as the first step toward embedding business intelligence directly into financial planning workflows.

The update introduces real-time, customizable dashboards designed to provide finance teams with deeper visibility into operational and financial data without requiring external BI tools. The dashboards also lay the groundwork for a broader roadmap that will introduce AI-powered analytics and automated insights later in the year.

For finance teams operating in mid-market organizations, the shift could reduce the friction between planning, analysis, and executive reporting.

Bridging the Gap Between Planning Tools and Business Intelligence

Traditional FP&A workflows frequently involve multiple systems. Finance teams create budgets and forecasts within planning tools, export financial data to spreadsheets, and then rebuild reports in separate BI platforms before presenting insights to leadership.

This fragmented workflow creates inefficiencies that many organizations accept as part of financial planning.

Centage’s new dashboard functionality aims to consolidate those steps within a single environment.

The updated dashboards allow finance professionals to build visual reports directly inside the platform, pulling real-time data from integrated enterprise systems. Executives can access dashboards without waiting for manual report preparation or data refreshes before meetings.

The change represents a broader evolution in finance technology where analytics capabilities are increasingly integrated into operational platforms rather than delivered through separate reporting systems.

A Series of AI Releases Leading to Embedded BI

The dashboard launch is part of a larger product roadmap that Centage has been executing throughout 2026.

Earlier this year, the company introduced an AI Integration Framework designed to simplify ERP system connectivity. The feature uses generative AI to automatically generate custom integration code for enterprise resource planning systems, reducing onboarding timelines from several weeks to a few days.

ERP integration has historically been one of the biggest obstacles for FP&A software adoption. Finance teams often wait weeks for technical teams to build data pipelines between systems.

With the AI Integration Framework, Centage says onboarding timelines can drop from eight to twelve weeks down to roughly 48 to 72 hours, allowing organizations to start analyzing financial data sooner.

Another release earlier this year introduced AI Account Group Mapping, a feature designed to streamline general ledger configuration.

Finance teams typically spend weeks mapping general ledger accounts when implementing planning software. The AI-powered mapping tool reduces that process to a single automated step, allowing the system to categorize accounts in minutes.

Together, those updates signal a broader strategy focused on reducing manual configuration and accelerating financial data accessibility.

Real-Time Dashboards Become the Foundation Layer

The newly released dashboards expand on those AI-driven capabilities by introducing a visual analytics layer directly inside the FP&A platform.

The updated interface includes:

• customizable data visualizations
• real-time financial metrics
• streamlined connections to ERP systems
• dashboards designed for both analysts and executives

The platform integrates with widely used enterprise systems including NetSuite and other financial data sources, allowing organizations to visualize operational performance alongside financial planning models.

Finance teams can now create executive-ready dashboards without exporting data into presentation tools or rebuilding reports manually.

The release also reflects a design shift toward user experiences that serve both analysts building financial models and executives consuming summarized insights.

In practice, that means finance leaders can access live financial metrics without waiting for periodic reporting cycles.

A Product Strategy Focused on Continuous Delivery

The dashboard update is the latest in a series of product releases from Centage over the past year.

In March 2025, the company introduced Worksheets, a feature designed to replicate the flexibility of spreadsheet modeling within a governed planning environment. The feature allows finance teams to perform familiar spreadsheet-style analysis while maintaining centralized data control.

Another release, the Spread Method Wizard, introduced a visual workflow designed to simplify budgeting allocations—one of the more repetitive tasks in financial planning.

Meanwhile, real-time payroll integrations connected workforce data directly to planning models. Because labor costs often represent the largest operational expense for many organizations, direct payroll integration allows finance teams to model workforce changes more accurately.

The platform also introduced Maestro, an AI-powered FP&A assistant designed to help finance professionals navigate financial models, locate data, and surface insights faster.

These releases collectively illustrate the company’s broader strategy: combine automation, AI capabilities, and usability improvements to simplify financial planning workflows.

Finance Software Enters the Era of Embedded Intelligence

Centage’s roadmap aligns with a broader shift underway across enterprise software platforms.

Historically, companies relied on dedicated BI tools for analytics and visualization. Platforms such as Microsoft’s Power BI, Tableau, and Qlik became essential tools for transforming raw data into insights.

But a growing number of software vendors are embedding analytics directly into operational applications.

The approach—often described as embedded business intelligence—allows users to analyze data within the context of the systems where that data originates.

In finance software, this trend means planning platforms are beginning to incorporate visualization, reporting, and predictive analytics capabilities that previously required separate tools.

The result is a more integrated workflow where planning, reporting, and analysis occur in the same environment.

The Bigger Picture: AI Reshapes Financial Planning Tools

The push toward embedded BI also reflects broader changes in enterprise finance technology.

Finance teams increasingly expect planning tools to deliver real-time insights rather than static reports.

According to research from Gartner, organizations are investing heavily in advanced analytics capabilities that allow finance departments to move from historical reporting toward predictive forecasting and scenario modeling.

Meanwhile, IDC estimates that global spending on analytics and business intelligence platforms continues to grow steadily as companies prioritize data-driven decision-making.

Artificial intelligence is accelerating this transition.

AI-driven analytics tools can automatically detect patterns, flag anomalies, and generate recommendations based on financial data. Instead of manually analyzing spreadsheets, finance professionals increasingly rely on automated systems that surface insights in real time.

Centage’s roadmap suggests the company aims to integrate these capabilities directly into its FP&A platform.

Upcoming releases include mobile dashboards that allow finance leaders to access reports on the go and AI-powered analytics designed to identify trends or anomalies within financial data automatically.

Top Insights

• Centage has launched enhanced real-time dashboards designed to embed business intelligence capabilities directly into its FP&A platform for mid-market finance teams.

• The dashboard update builds on earlier 2026 releases including the AI Integration Framework and AI Account Group Mapping, both designed to accelerate ERP integration and financial data setup.

• The new dashboards allow finance teams to create executive-ready visual reports directly within the platform without exporting data into separate BI or presentation tools.

• The release establishes the foundation for upcoming AI-powered analytics capabilities that will surface trends, anomalies, and strategic insights from financial data.

• Embedded business intelligence is emerging as a key trend in enterprise software as companies integrate analytics directly into operational platforms.

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