Summary Bullets:

• Salesforce has integrated Slackbot more deeply into its platform, providing access purportedly to the entire Salesforce ecosystem.

• Despite positives the announcement generates concerns, the most pressing regarding security.

Salesforce has greatly extended the scope of Slackbot, the AI-driven personal work agent built into Slack, claiming it now spans the entire Salesforce platform. The change will add substantial value, keep Slack – the company – competitive with rivals, and cement the starring role Slack has come to play at Salesforce.

The new and improved Slackbot advances if not completes Slack’s emergence as a key member of the Salesforce organization. When acquired by Salesforce in 2021 Slack seemed destined to fall into a black hole, a Jonah being swallowed by the whale. Instead, it has been methodically elevated into a central gateway of the Salesforce platform. Slack has been increasingly embedded into Salesforce’s broader product fabric, positioned as the front end for Salesforce’s AI ecosystem and now evolving into the default collaboration interface for the Salesforce platform. Slack has been granted a new and better life by its parent.

In addition to accelerating its rebirth, the enhanced Slackbot benefits Slack by bringing greater value to users and keeping it neck-and-neck with rivals such as Cisco and Zoom, who are infusing their own platforms with the same type of cross-pollination.

This latest version of Slackbot enables users to get work done far more effectively by serving as a unified front across the Slack and Salesforce platforms. At the heart of the rejuvenated Slackbot lies MCP servers from Salesforce, the fuel behind the Salesforce ‘Headless 360’ initiative which seeks to harness capabilities anywhere in Salesforce and funnel them into Slack. Slackbot now acts as a conductor, overseeing an orchestra consisting of Salesforce products, enterprise data, third-party applications, and AI agents.

At a most basic level, users provide Slackbot a request through a natural language interface, and Slackbot fulfils it by pulling together relevant resources such as conversations, files, and data residing in multiple, often far-flung repositories. Users can, for example, update sales pipelines and surface next best actions, discover whether the marketing team is on track to achieve a forecast, or route a service case to the appropriate individuals. Over time, Slackbot gets to know users better, thus fulfilling their needs with greater speed and accuracy.

Despite the positives, there are some concerns associated with the announcement. The largest involves security. The security posture behind Slackbot is an open question and one with serious implications especially given the pooling and sharing of data which Slackbot facilitates; Salesforce needs to articulate clearly what types of safeguards are in place. Another concern is the lack of contact center capabilities to complement the collaboration capabilities found in Slack; a robust contact center portfolio has become critical for remaining competitive in the market. Last, despite rapidly accumulating AI-driven features on its platform and its association with Salesforce, the Slack name lacks the brand equity enjoyed by competitors. The likes of Cisco and Microsoft were well known in team collaboration well before the pandemic, and Zoom became a household name when it hit. Slack has not achieved the same notoriety.

If Salesforce can promptly address each of these issues, it could merit inclusion among the top players such as Cisco, Microsoft, and Zoom.

The post Slackbot Spreads Its Wings but Questions Remain appeared first on IT Connection.

Summary Bullets:

• Boomi is evolving from an iPaaS into an enterprise platform combining integration, automation, API management, data management, and AI agent governance.

• GlobalData recently attended Boomi’s World Tour London 2026, where agentic AI was discussed at length around announcements including Boomi Connect, Boomi Orchestrate, and Boomi Companion.

Although Boomi has historically been best known as an integration platform as a service, or iPaaS, the company is going to great lengths to emphasize that it has evolved into an enterprise platform which activates data and workflows for customers and combines integration, automation, API management, data management, and AI-agent governance. The Boomi platform acts as the connective and orchestration layer between an organization’s applications, data, and AI systems, but is increasingly moving towards management of AI agents to help data enhance business processes.

The company is investing significant resources in its Runtime environment, a hybrid platform that customers can install either locally or in a virtual private cloud. Integration is an area of major focus for the vendor, with plans to bring all business workloads into Runtime, including workflows, AI agents, and eventually small language models. Boomi has a partnership with Red Hat to help manage the deployment of open-weight and proprietary models.

Boomi is not tied to a particular ecosystem, in the vein of providers such as ServiceNow; rather, it offers an independent API control pane across all ecosystems. For example, it can connect Salesforce with SAP, synchronize customer records, automate an order-to-cash process, expose the process as an API, send transactions to suppliers through EDI, and now help AI agents replicate the same process.

The company is expanding not just beyond integration but across all platform services including investments in data readiness with Meta Hub, with strong traction among customers thanks to the growing popularity of data management systems. Currently in preview, the Knowledge Hub will also allow customers to bring unstructured data into the platform.

In the realm of agentic solutions, Boomi has recently announced new products including Boomi Connect, Boomi Orchestrate, and Boomi Companion:

• Boomi Connect offers the governance layer, sitting between the AI layer and the enterprise applications in the customer organization, with secure access, tool scoping, and observability, connecting and integrating MCP and governance by creating a single stack for CSOs. It establishes secure connections between AI tools (Claude, Copilot, and Gemini) and enterprise applications thanks to more than 1,000 MCP-enabled tools.

• Boomi Orchestrate brings IT, business applications and agents together to solve complex problems by creating blueprints allowing customer teams to build solutions. While agentic platforms are quickly becoming commoditized, Boomi has focused on delivering its proprietary offering in a way that meets customer requirements.

• Boomi Companion enables existing AI tools to design, build, test, deploy, and diagnose Boomi integrations in natural language. It transforms prompts into integrations in any language the AI agent supports and offers AI-assisted development with Claude Code, Cursor, and more via open-source Agent Skills standard.
Boomi is also launching Boomi Prompt, although the release date is yet to be determined. Boomi Prompt will form a layer of intelligent routing that is not limited to routing the LLM but will route, sort out, and separate deterministic from probabilistic workflows so users do not waste tokens. This promises, when it comes out, to be a strong portfolio addition to help customers mindful of “tokenomics”, the management of costs driven by AI consumption.

Agent Studio, introduced last May, is an agent management platform for customers who have been undertaking integration processes for 20 years and do not want to start over with agents and replace everything. These types of enterprises are looking for slightly augmented intelligence to leverage agents for fixing things that are not working. Rather than starting over, they favor an integration process for testing applications. Customers are used to deterministic workflows and the Agent Studio offers an integration workflow in an structured form.

Boomi is focusing on the right objectives. In terms of governance, the company is in a solid position to benefit from a significant opportunity in the next two years as token budgets get out of control to help people to get back into deterministic processes and bring non-deterministic workflows back under control.

The caveat is that the portfolio is becoming very broad. Integration remains Boomi’s most mature and recognizable capability, while advanced data engineering, enterprise knowledge and agent-management products are newer expansion areas. Many customers may still look at the Boomi platform primarily as an enterprise connectivity and orchestration platform, but its advancements in agentic AI management should not be overlooked.

The post Boomi Targets Agentic AI Governance, but Orchestration Remains Its Raison d’Etre appeared first on IT Connection.

Summary Bullets:

• Fast-growing use of agentic AIs within organizations has triggered agentic orchestration/governance prioritization among platform providers

• Controversy remains over two distinct approaches to orchestration: control plane construct or orchestration frameworks

Enterprises deploying AI in 2026 are turning their attention from deployment of agentic AIs to the management of growing numbers of agents being released across organizations. Companies are struggling with how to manage the hundreds or thousands of individual agents built within their organizations–agents built by different teams, running on different platforms, with inconsistent security and governance. This is problematic, considering most organizations lack visibility into agent inventory, purpose, and authorization.

The practice of addressing agentic orchestration at the control plane platform layer is moving to the forefront of the conversation, spurred by the lack of visibility, security, and management associated with agentic sprawl. Control planes sit above the agent layer, governing, observing, and enforcing policy across agents regardless of where they originated. The advantage is in their ability to ensure identity and security enforcement and enable cross-vendor interoperability regardless of what framework they use for coordinating agents. This approach contrasts with orchestration frameworks which are features of agentic solutions that simply coordinate agents.

GlobalData’s research captures the scale of the agentic market, and therefore the urgency of the situation. The report “Market Opportunity Forecasts to 2029: Agentic AI” puts the global agentic AI market at a 50.6% CAGR for 2024–2029, reaching $45.4 billion by 2029, driven by enterprise demand for autonomous decision-making, multi-agent orchestration, and scalable cloud-native AI infrastructure. GlobalData reports that early adopters are even replacing traditional robotic process automation (RPA) with goal-driven, self-adapting agent systems — and that the shift from pilots to production-grade systems is accelerating.

Vendor Strategies

A control plane market is emerging, positioned as framework-agnostic. Leading AI and platform providers are announcing strategies and solutions to address this evolving branch of agent orchestration:

• IBM is positioning the next generation of watsonx Orchestrate as an agentic control plane for the multi-agent era. It supports IBM-native agents alongside LangGraph, Langflow, and agents built on the open A2A protocol, with consistent policy enforcement.

• Salesforce has built its orchestration strategy on MuleSoft’s Agent Fabric. This has been helped by its ability to consolidate multiple data sources into a single source following Salesforce’s Informatica acquisition last November. A trust and data security layer serves as the key component of its new Agent Fabric control plane.

• ServiceNow is featuring its AI Control Tower as the governance layer spanning every AI agent, model, and action running across the enterprise, regardless of which vendor built them. The company is repositioning from being a workflow automation vendor to an enterprise AI operating system, shored up by its recent acquisition of IT/OT security provider Armis, which leans heavily into its new AI Control Tower solution.

• Boomi’s control plane approach is addressed via the Boomi Enterprise Platform, which sits between disparate systems, agents, frontier models, and data sources. Boomi’s acquisition of Lunar.dev, AI/MCP gateway, plays heavily into its strategy as the prompt routing layer for governing MCP servers and access.

Yet controversy over how to govern the fast-growing agentic AI market segment remains. Some rival platform providers are taking a different tact and keeping agentic orchestration within the confines of their own platforms and product ecosystems. They are not positioned as supporting cross-vendor governance layers in the same way as competitors:

• Microsoft has been reshaping Copilot Studio from an agent-building tool into an agent governance layer. It describes the new governance features as having centralized policy enforcement, agent lifecycle oversight, and cross-ecosystem governance spanning Microsoft 365 and partner-built agents. However, Microsoft’s architecture is embedded in and distributed across its popular platforms, including Power Platform and Azure, versus a discrete, specific control plane layer that sits above disparate agents.

• Oracle OCI’s strategy for management and governance also currently bypasses a control plane architectural model and remains within the confines of its own ecosystem. OCI Enterprise AI embeds agentic orchestration natively as a feature across the Oracle technology layers rather than positioning a discrete governance layer above them. Enterprise AI’s three integration layers are: Enterprise AI Models, Enterprise AI Agents, and Enterprise AI Governance.

Summary
The concept of a control plane architecture construct is still being defined by the market. Vendors operating in the agentic orchestration space have varying opinions and product strategies. Pioneering activities and offerings suggest this type of AI operating system will quickly become the fundamental layer for agentic AI. Operational guardrails are critical for bringing to production environments that are built around ambitious agentic AI projects.

It is worth noting that players in this market segment have generally adopted or endorsed MCP and A2A as the underlying interoperability layer, serving as the common protocol layer, while the control planes above it remain proprietary and competitive. Therefore, much of the agentic AI battle will be won or lost according to who controls the management, orchestration, and governance of disparate agents across enterprise environments.

For more on this topic and other cloud trends including escalating cloud costs, please see Cloud Watch Q2 2026: Reassessing On-Demand Economics in the Era of Escalating Cloud Costs

The post Lack of AI Agent Oversight Brings Dueling Approaches appeared first on IT Connection.

Summary Bullets:

• Cycles between advanced AI model rollouts are significantly shortened among leaders in this space

• Developers are gaining access to agentic-injected integrated development environments (IDEs); while knowledge workers gain access to agentic AI assistants.

The second quarter marks a momentous period in the industry’s ongoing AI efforts. Platform leaders shipped next-generation agentic runtimes including autonomous and other advanced capabilities, all while managing a more compressed cycle of new AI models, which are rolling out in a matter of weeks versus months.

A few notable announcements highlight this structural shift in how enterprise AI is built, deployed, and presented to enterprises.

Microsoft’s long-awaited private review of its first in-house reasoning model, MAI-Thinking-1, an enterprise-grade medium-weight model that promises to shake up the industry in a number of ways. Microsoft is going up against the industry’s strongest models based on the strength of its mathematical and scientific reasoning abilities, for improved training loops, citing numerous Microsoft-backed engineering benchmark tests. It is taking on Claude Sonnet 4.6 and Opus 4.6 by claiming lower token costs and smaller inference footprint. For the first time since the beginning of its relationship with OpenAI, Microsoft is able to break into the enterprise space with its own AI model, on par with leading rivals. Microsoft’s win will inevitably be at the expense of OpenAI.

Expanding its AI portfolio further was the June release of Microsoft Copilot Studio – Computer Use, revamping AI assistants to perform further up the agentic AI stack. The release supports the use of computer-use agents directly in Copilot Studio, helping bypass integrations with APIs in order to develop workflow automations.

To keep pace with top rivals Google and Anthropic, OpenAI announced its biggest model release yet, GPT-5.5, emphasizing its strengths in agentic coding, scientific research, and the ability to automate tasks associated with knowledge work. As the industry’s early GenAI leader, OpenAI has been challenged to maintain its innovative prowess.

OpenAI’s newest advancements are mere weeks following its last GPT release, demonstrating the staggering breakneck pace AI model providers are compelled to maintain to keep up in this highly competitive segment. OpenAI is hoping to win back the loyalty of professional coders who have moved to Anthropic Claude in droves for its accuracy in coding. OpenAI has been most popular among consumers, while competitors, including Google and Anthropic, have gained more traction in the enterprise space.

AWS’s latest AI announcements demonstrate a deliberate pivot towards agentic AI amidst an increasingly competitive landscape. Under mounting competitive pressure, Amazon is investing heavily in tools that span developer and non-developer audiences.

The newly announced Amazon Quick agentic AI assistant is a revamp of the GenAI assistant Q Business platform, providing knowledge-based workers with insights while also being able to act and automate repetitive workflows. Quick connects internal data across AWS services, third-party platforms, and on-premises systems. Other key announcements were Kiro agentic IDE built on Code OSS and powered by Claude models, via Amazon Bedrock; and Bedrock AgentCore, serverless runtime, and AgentCore Harness, which let developers build and run production-grade AI agents quickly without needing to code custom orchestration loops.

The post AI Wars Intensify via Major LLM/Agentic Releases appeared first on IT Connection.