Agentic AI Is Rewriting Enterprise IT Playbooks

Agentic AI for enterprise applications is moving from concept to the center of corporate IT strategy. Companies such as Oracle, IBM and Salesforce are racing to embed autonomous agents into business apps, marketplaces and collaboration platforms. Therefore, executives must understand how these moves affect automation, integration and talent. This post explains recent announcements, why they matter, and what leaders should watch next.

## Agentic AI for Enterprise Applications: Oracle's Platform Push

Oracle has stepped up its agentic strategy by expanding its agentic AI platform with new features. According to coverage, the move is part of a broader AI software strategy that complements Oracle’s ambitions in AI hardware and infrastructure. In short, Oracle is not just selling chips and cloud capacity. Instead, it is building software layers that let enterprises design, deploy, and scale AI-driven agents inside their systems.

Why this matters: enterprises often struggle to connect automation to real business applications. Oracle’s platform efforts aim to bridge that gap. Therefore, companies that already use Oracle’s Fusion Applications or Oracle Cloud Infrastructure may find faster, more integrated paths to embed agents in finance, HR, supply chain and other domains. Additionally, an expanded platform can attract partners who build and validate agents for specific industry needs.

Impact and outlook: Expect more agent marketplaces, prebuilt agent templates, and vendor partnerships that accelerate deployments. However, success depends on interoperability, governance, and the ability to connect agents to real enterprise data. As Oracle builds both infrastructure and software, customers may gain simpler, end-to-end options for agentic AI — but they should evaluate lock-in and integration costs carefully.

Source: AI Business

Agentic AI for Enterprise Applications: Slack as an Agentic OS

Salesforce is positioning Slack to become an "Agentic OS" — a central place where humans, agents and AI collaborate. The company’s vision treats Slack not only as a messaging workspace but as a host for AI assistants that can act on behalf of teams. Therefore, Slack could become the UI layer for agentic workflows across tools.

What this means for businesses: Many organizations use Slack for communications. Consequently, adding agent capabilities there shortens the distance between insight and action. For example, an agent in Slack could surface a contract alert, summarize a customer thread, and propose next steps — all inside the same interface. Additionally, vendors and internal IT teams could build agents that connect Slack to CRM, ERP, and ticketing systems.

Enterprise impact and vendor strategy: This repositioning pressures other collaboration platforms to add similar agent features. It also changes integration priorities. Instead of pushing agents into back-end systems only, companies will plan for conversational and action-oriented agent experiences. However, teams must also design governance and privacy controls, because agents operating inside Slack will see sensitive conversations and workflows.

Future outlook: If Slack becomes an agentic OS, adoption could speed because users already live there. Yet, companies will need clear policies and standards for agent behavior, approvals, and audit trails. Therefore, treat Slack-based agents as both productivity tools and governed enterprise services.

Source: AI Business

Agentic AI for Enterprise Applications: IBM’s Agents on Oracle’s Marketplace

IBM announced three new AI agents available on the Oracle Fusion Applications AI Agent Marketplace. These agents were built with Oracle AI Agent Studio and aim to automate common workflows inside Oracle Fusion Cloud Applications. In addition, IBM plans complementary agents for HR and supply chain built with IBM watsonx Orchestrate.

Why this matters: Marketplaces make it easier for customers to discover validated agents. Therefore, enterprises running Oracle Fusion applications can find IBM-built agents that are tested and integrated. Also, IBM’s plan to use watsonx Orchestrate as a multi-agent supervisor means organizations can coordinate agents across Oracle and non-Oracle systems. Consequently, agents can work together rather than in isolation.

Operational impact: For IT and business teams, validated marketplace agents reduce development time. Additionally, agents that automate routine tasks can free staff for higher-value work. However, companies must ensure these agents are configured to match process and compliance requirements. Moreover, orchestration across multiple agents and systems calls for clear data access and governance controls.

Outlook: Expect more joint offerings from large vendors and consulting firms. Marketplaces will grow as a distribution model for enterprise agents. Therefore, buyers should evaluate agents for fit, security, and the ability to orchestrate across tools.

Source: IBM Think

Cognitus Deal: How Services and M&A Accelerate Agentic Workflows

IBM’s planned acquisition of Cognitus underlines a strategic move to strengthen SAP transformations with AI-enabled services and accelerators. Cognitus brings SAP S/4HANA expertise, industry-specific assets, and AI-powered tools for tasks such as data migration, contract lifecycle management, and real-time billing.

Why acquisitions matter now: Agentic AI for enterprise applications needs more than models and interfaces. It needs domain knowledge, industry workflows, and software that fits regulated environments. Therefore, buying companies with proven capabilities can speed delivery and reduce risk. Additionally, Cognitus’ SAP assets are designed to be plug-and-play, which helps firms modernize more quickly.

Enterprise impact: Clients in complex industries — like aerospace, defense, utilities and government contracting — often face strict compliance and unique processes. Consequently, combining IBM’s scale with Cognitus’ domain software can help deploy agentic agents that respect regulations and deliver measurable value. Furthermore, IBM’s consulting platform and delivery frameworks may help scale these solutions globally.

Looking forward: Mergers and partnerships will likely continue as vendors race to offer complete solutions: agents, integration, governance, and industry accelerators. Therefore, CIOs should watch how acquisitions change vendor roadmaps and service models. In practice, expect bundled offerings that reduce project complexity and accelerate agentic AI adoption.

Source: IBM Think

Fast-Tracking Talent: IBM and Mission 44’s Skills Push

IBM’s partnership with Mission 44, Lewis Hamilton’s foundation, focuses on fast-tracking AI skills via IBM SkillsBuild. The program aims to create learning pathways in AI, cloud, and data for students and communities, starting with activations at Formula 1 events and expanding into year-round content.

Why skills matter: Agentic AI for enterprise applications requires people who can design, integrate, and govern agents. Therefore, workforce development is not optional. Organizations that lack trained talent will struggle to adopt and maintain agentic systems. Additionally, broadening the talent pool increases diversity of thought and helps tackle practical deployment challenges.

Program impact: IBM SkillsBuild offers free training for students and adults. In collaboration with Mission 44, it will deliver immersive, hands-on experiences and F1-themed content to spark interest in STEM. Consequently, these programs create a pipeline of people who understand AI concepts and enterprise needs. Furthermore, tying skills programs to real-world scenarios helps learners become job-ready faster.

Outlook for enterprises: Companies should partner with skilling initiatives and invest in internal reskilling. Therefore, expect more public-private programs that align education with enterprise requirements. In the near term, combining technology investments with skills programs will be the differentiator for organizations seeking to deploy agentic AI successfully.

Source: IBM Think

Final Reflection: Connecting Platforms, Marketplaces, M&A and Skills

Taken together, these announcements show a clear pattern. First, platform expansion (Oracle) and UI plays (Salesforce/Slack) aim to make agents visible and usable where people already work. Second, marketplaces and validated agents (IBM on Oracle Marketplace) lower adoption barriers and create a distribution model for ready-made automation. Third, targeted M&A (IBM and Cognitus) supplies domain expertise and industry accelerators that agents need to be useful in regulated environments. Finally, skills programs (IBM and Mission 44) ensure organizations can staff and govern agentic systems responsibly.

Therefore, the enterprise shift is about assembling four pieces: platform, distribution, industry implementation, and human capital. As a result, leaders should adopt a pragmatic approach. Start with high-value, well-governed agent pilots. Then, prioritize integration, vendor choice, and talent development. In the end, agentic AI for enterprise applications promises real productivity gains. However, success will depend on measured adoption, governance, and continuous investment in people.