As organizations recalibrate their digital strategies for 2026, the rise of AI agents will unequivocally reshape the Salesforce ecosystem. What began as conversational copilots has rapidly evolved into a new class of operational actors capable of executing work, orchestrating complex processes, and scaling business functions that once depended entirely on human intervention.

Agentforce (Salesforce’s agentic AI platform) is emerging as the backbone of this shift. And as adoption accelerates, organizations are looking for partners with the technical depth, governance expertise, and industry context to deploy these agents responsibly and drive measurable value.

Below is a comprehensive look at the five macro-trends defining the Agentforce and AI-agent landscape heading into 2026. See what the future holds for organizations modernizing on Salesforce.

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1. Operational autonomy will become the enterprise baseline

AI agents are no longer confined to advisory roles. In 2026, operational autonomy is becoming normal best practice for scaling organizations. By outsourcing tedious and often mindless tasks to AI, it frees up teams to focus on relationships and value. Companies that are implementing agents are seeing faster results and better quality as workloads are redistributed.

Modern AI agents can:

Execute workflows end-to-end with minimal human touch
Trigger and complete actions directly in Salesforce (Lead updates, Case routing, task creation, approvals)
Scale repetitive or high-volume workstreams beyond human capacity

For Salesforce customers, this means AI is shifting from a “productivity enhancer” to a force multiplier that compresses cycle times, increases throughput, and eliminates process friction.

The key to maximizing the value of these agents is to work with experts who know how best to deploy them. There are some out-of-the-box options for agents, and these will likely get better with time, but businesses should invest in proper implementation. It’s important to build effective automation frameworks to align governance, auditability and data hygiene so Agentforce can operate with confidence in any workflow.

As of right now, most organizations are still in the experimentation or piloting phase. Nearly two-thirds of respondents say their organizations have not yet begun scaling AI across the enterprise. But that is a natural next step in this process. As soon as companies start to get more familiar with these technologies, operational autonomy is inevitable.

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2. Multimodal interaction will unlock adoption across the workforce

What do we mean by multimodal interfaces? This includes things like voice, visual input, structured data, natural language and more. And Agentforce’s evolution into these interfaces is democratizing access to AI to make it easier for businesses to hit the ground running.

Teams can now:

Speak to agents during field work
Upload documents for automated analysis and synthesis
Trigger workflows via simple prompts instead of technical navigation

This breaks down adoption barriers and extends AI utility beyond technical roles into frontline operations, service centers, and non-desk teams.

When McKinsey conducted a survey on AI, they found 62% of survey respondents say their organizations are at least experimenting with AI agents. Full-scale adoption is right on the horizon. We design intuitive, cross-channel interaction models that meet users where they are, reducing change-management friction and driving sustained adoption across business units.

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3. Multi-Agent orchestration will become the new operating model

Organizations are moving past single bots and toward orchestrated networks of specialized agents. Whereas bots require a lot of manual programming and have limited responses, agents can pull data and craft unique responses based on individual queries. Having all your data connected and centralized for these agents to pull from will be more important than ever.

What does this look like in application? A few examples might include:

A research agent gathering customer information
A drafting agent generating outreach messaging
A QA agent validating accuracy against policies
An execution agent updating Salesforce and sending communications

This multi-agent architecture enables complex, multi-step processes — from onboarding to marketing execution — to run autonomously and reliably. Data 360 acts as the foundation for many of these agents, so ensuring all the information is accurate and up-to-date is critical.

When setting up a multi-agent infrastructure, it’s necessary to create agent ecosystems with clearly defined responsibilities, escalation logic and oversight layers. We want these agents working together, contributing to a cohesive operational flow. Shortcutting this step will only bring more friction and challenges down the road.

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4. Verticalization will drive better outcomes

As the market matures, organizations are moving away from generic agent templates and toward industry-specific AI agents. This is true with the development of any new technology on the market. You start with a general baseline, and you figure out how it best fits into your own ecosystem.

What might that look like?

Financial services agents aligned to compliance frameworks
Manufacturing agents built to manage inventory, logistics, and service cases
Public sector agents with embedded policy constraints
Retail agents orchestrating omnichannel service and personalization

The performance gap between generic and verticalized agents is widening, making industry experience a critical differentiator.

Let’s take a look at a few examples of some agents we’ve built recently for specific industries. The first one is for financial institutions. This QuickQual agent is able to quickly identify qualified customers and streamline the process.

Or how about agents that understand the complexity and challenges of the recruitment and admission process for universities? There’s an agent that can help students with inquiries by pulling information from their existing data.

Or how about an agent that actually helps the customer, rather than providing generic responses? The service agent can pull information from the existing data to provide accurate, instant answers to your customers.

TELUS Digital brings industry-focused solutions — integrating industry logic, regulatory requirements, and Salesforce best practices directly into the agent design.

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5. Governance, security, and risk will become executive mandates

Agentic AI is moving from peripheral tooling to a core component of enterprise execution. As that shift accelerates, boards and CROs are elevating governance from a peripheral consideration to a non-negotiable operational requirement. The days of experimenting with agents in siloed sandboxes are over. Organizations now need robust, advanced guardrails that can withstand regulatory scrutiny, internal audit, and real-world usage at scale.

Three pressure vectors are driving this shift:

A. Non-human identities are now part of the enterprise stack

AI agents can read and write CRM data, update records, trigger automations, and interact with customers. This introduces a new identity class that must be managed with the same rigor applied to employees and system accounts.

Key challenges include:

Provisioning and deprovisioning non-human identities
Defining fine-grained permission sets to constrain agent actions
Preventing privilege creep as agents gain expanded responsibilities
Maintaining traceability across every action an agent takes

The governance footprint is expanding, and organizations need to implement controls before autonomous execution scales beyond their ability to manage it.

B. Regulatory and ethical compliance standards are tightening

In financial services, healthcare, and public-sector environments, regulators are already signaling heightened expectations. Data lineage, auditability, explainability, and consent management are becoming table stakes, particularly as agents begin interacting with PII, transactional data, and customer communications.

Leaders must ensure:

Decision pathways are transparent and reviewable
Agents adhere to approved business logic and policy boundaries
Escalation processes are in place when agents encounter uncertainty
Data usage complies with jurisdictional requirements and industry mandates

Without these guardrails, enterprises expose themselves to operational, reputational, and legal risk.

C. Drift, deviation, and misalignment require continuous monitoring

As agents become self-directed, the risk isn’t malicious behavior, but subtle deviation from expected patterns. Small inaccuracies compound quickly at scale. That means real-time monitoring must be embedded into the operating model.

This includes:

Continuous evaluation of agent output quality
Automated exception detection
Real-time alerts when agents produce anomalous behavior
Feedback loops to refine or retrain agents based on new data

Enterprises can no longer rely on manual checks or ad-hoc reviews. They need proactive oversight frameworks capable of intervening before errors cascade.

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What this means for Salesforce customers in 2026

The shift to agentic operations represents a shift past incremental enhancements toward a wholesale redefinition of how organizations execute work on Salesforce. There will likely be more challenges and learning curves associated with these new agents, but the outcomes are worth the investment. Some of the key implications include:

Lower operational cost-to-serve through scalable automation
Faster decision cycles with real-time, AI-driven execution
Increased workforce leverage as human teams focus on strategy and high-value interactions
Stronger customer experiences driven by consistent, automated, cross-channel engagement

Organizations that treat agent deployment as a strategic transformation (rather than a tactical experiment) will unlock disproportionate competitive advantage.

TELUS Digital has deep experience deploying Salesforce solutions at enterprise scale. As Agentforce becomes a core component of the Salesforce platform, customers need partners who can support specific industry and technology requirements.

Our approach is centered on accelerating value realization while protecting operational integrity — ensuring AI agents are an asset, not a liability. Reach out to our experts today to see how you can get ahead of 2026 trends.

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AI Agents in 2026: How Agentforce will redefine enterprise execution