7 Enterprise AI Solutions Helping Teams Work Smarter in 2026

A business can invest in the best productivity software available and still struggle with inefficient workflows. Employees may have access to project management tools, cloud storage, communication platforms, customer databases, and internal documentation, yet finding a reliable answer often requires checking several of them.

This problem becomes more complicated as organizations grow. Information accumulates across departments, employees develop different ways of documenting work, and important decisions become buried in old conversations. The result is wasted time, duplicated effort, and unnecessary interruptions between teams.

Enterprise AI solutions offer a different approach. By connecting information with intelligent assistance and automation, they can help employees spend less time gathering context and more time applying it.

From workplace AI platforms to specialized business assistants, here are seven solutions worth exploring.

1. Glean: Connecting People, Knowledge, and Work

The challenge with enterprise information is not always a lack of data. Often, the information employees need already exists, but it is scattered across too many applications to access easily.

Glean takes a cross-platform approach to workplace AI. Its platform connects information from business applications to help employees search company knowledge, ask questions, generate content, and use AI agents for selected tasks.

Glean's enterprise search helps employees find information across connected applications rather than searching each system individually. Its workplace AI capabilities use organizational context to make answers more relevant to employees' work.

For example, a sales representative preparing for a customer meeting might need account history, product updates, and notes from previous conversations. An engineer investigating a technical issue might need documentation, incident reports, and colleagues' discussions.

By bringing relevant information into a single search-and-assistance experience, Glean can reduce the effort required to gather this context.

Best for: Organizations looking for a cross-platform workplace AI solution that connects company knowledge and helps employees find answers across multiple business applications.

Consideration: Its value depends on how well it connects to the organization's existing systems, how relevant its results are, and whether its capabilities justify the implementation and licensing costs.

2. Microsoft 365 Copilot: Bringing AI Into Everyday Office Work

Microsoft 365 Copilot integrates AI assistance into familiar productivity applications, including Word, Excel, PowerPoint, Outlook, and Teams. Depending on the application and available features, employees can use it to draft documents, explore spreadsheet data, prepare presentations, summarize meetings, and manage email.

For example, a project manager could use Copilot to summarize a Teams meeting and identify action items, then use that context to prepare a project update. A finance team might use its Excel capabilities to explore data or help understand a formula.

The main advantage is its close relationship with the Microsoft 365 environment. Organizations already using Microsoft applications may be able to introduce AI into familiar workflows instead of asking employees to adopt an entirely separate platform.

However, results depend on data quality, access permissions, configuration, licensing, and the particular Copilot features available to users.

Best for: Organizations that rely heavily on Microsoft 365 and want AI assistance within their existing document, spreadsheet, email, and meeting workflows.

Consideration: Businesses should assess licensing costs, information governance, and how well their Microsoft 365 environment is organized before rolling out Copilot broadly.

3. Google Gemini: Supporting AI-Powered Collaboration

Google Gemini brings AI capabilities into supported Google Workspace experiences, including Gmail, Docs, Sheets, and other collaboration tools. Depending on the features enabled, employees can use it to draft content, summarize information, analyze data, and develop ideas.

Its usefulness becomes clearer when considered in the context of everyday collaboration. A marketing team, for instance, might use Gemini to develop a campaign brief, summarize relevant information from selected company files, and organize ideas for a planning document. A team working with spreadsheets could use available AI features to help explore and organize data.

Google continues to expand Gemini's capabilities across Workspace, including assistance with tasks that involve multiple applications. However, the precise features available can vary by subscription, rollout status, administrator settings, and region.

For organizations already working in Google's ecosystem, Gemini offers a way to bring AI into familiar collaboration processes. It is less compelling as a reason to change productivity platforms unless its broader capabilities meet a clear business need.

Best for: Teams that use Google Workspace extensively and want AI support for writing, research, data analysis, and collaboration.

Consideration: Check which features are available under the organization's Workspace edition, how company data is handled, and whether the AI capabilities address specific workflow needs.

4. Amazon Q Business: Making Enterprise Information Easier to Use

Amazon Q Business is an AI-powered assistant designed to help employees find and use information across connected enterprise data sources. It can support internal question-answering, knowledge discovery, and content-related tasks using information available through configured integrations.

Consider an employee who needs to understand a company policy or locate information spread across documents and internal applications. Rather than searching each source separately, the employee can ask a question through the assistant and review the resulting information.

Amazon Q Business supports managed connectors for a range of enterprise applications and repositories. It also provides access controls intended to help ensure that responses reflect what individual users are authorized to access.

Its relevance is not limited to companies running their entire technology stack on AWS. The more important questions are whether the necessary data sources are supported, whether the integration meets security requirements, and whether the results are reliable enough for the intended tasks.

Best for: Organizations seeking an enterprise knowledge assistant that can connect information from multiple business systems, including companies with existing AWS infrastructure.

Consideration: Evaluate connector coverage, permission mapping, indexing requirements, deployment complexity, and pricing for the expected workload.

5. Salesforce Agentforce: Applying AI to Customer-Facing Workflows

Salesforce Agentforce enables organizations to build and deploy AI agents for defined business tasks. Its role is different from that of a general workplace search platform: it focuses on applying AI within business workflows, particularly those involving customer relationships and Salesforce data.

For example, a sales organization might explore agents that assist with prospect research or prepare relevant account information. A customer service team could evaluate agents for handling selected requests, gathering context, or supporting service workflows.

The extent to which an agent can act independently depends on its configuration, permissions, connected systems, and the controls established by the organization. Businesses should distinguish between tasks that an agent can perform automatically and tasks that still require human review or approval.

For organizations that already rely on Salesforce, Agentforce offers a way to explore AI-driven processes without treating AI as a separate destination outside their customer relationship management environment.

Best for: Businesses looking to introduce AI agents into sales, customer service, and other workflows built around Salesforce.

Consideration: Start with clearly defined use cases, assess the quality of customer data, and establish appropriate controls for actions affecting customers or business records.

6. ServiceNow Now Assist: Improving IT and Employee Services

ServiceNow Now Assist brings generative AI capabilities into ServiceNow's workflow platform. Its use cases include helping employees summarize service cases, draft responses, and work with information involved in supported service and operational processes.

An IT support team, for example, could use AI-generated summaries to understand an existing incident more quickly. Employee service teams might use assistance features to prepare responses or summarize requests before taking the next step.

The main distinction is its connection to service management and enterprise workflows. Rather than focusing primarily on searching all company knowledge, Now Assist supports activities within processes managed through ServiceNow.

The benefits depend on how the organization has implemented its service workflows and which Now Assist capabilities are available under its licensing and configuration.

Best for: Organizations already using ServiceNow for IT service management, employee services, or other enterprise workflows.

Consideration: Assess which repetitive tasks can genuinely be improved, how AI outputs will be reviewed, and whether implementation costs are justified by measurable improvements in service delivery.

7. Atlassian Rovo: Connecting Project Knowledge and Teamwork

Atlassian Rovo combines AI-powered search, chat, and agents to help teams discover and use information across Atlassian products and supported connected applications.

For teams using Jira and Confluence, project information is often spread across issues, documentation, discussions, and planning materials. Rovo can help employees find relevant context, ask questions about their work, and use agents for specific tasks.

For example, a project manager could look for related Jira issues and Confluence documentation before planning a sprint. A technical team could use search and chat to locate information about an earlier implementation decision or understand the history of a project.

Rovo's agents can also support defined activities, including creating or editing work items and documentation, where the necessary permissions and capabilities are available.

Its primary advantage is the connection between knowledge discovery and team workflows. Organizations using other project management platforms may find less value in adopting Rovo unless its supported integrations cover their needs.

Best for: Organizations that use Jira and Confluence and want to make project knowledge easier to find while exploring AI assistance within team workflows.

Consideration: Review available connectors, plan eligibility, administrative controls, and the tasks agents can perform in the organization's specific environment.

How to Choose the Right Enterprise AI Solution

The best solution depends on the work employees need to accomplish and where the organization's information currently resides.

Before making a decision, consider:

• Application coverage: Can the platform access the business systems employees rely on?
• Answer reliability: Does it produce useful responses grounded in relevant information?
• Security: Does it respect existing permissions and provide appropriate controls?
• Workflow support: Can it assist with the tasks employees actually perform?
• Implementation effort: Will integration, maintenance, and licensing fit the organization's resources?

A pilot involving several departments can reveal whether a platform solves real problems rather than simply adding another tool to the technology stack.

Final Thoughts

Workplace productivity depends on more than the number of applications a business uses. Employees also need a practical way to find information, understand context, and apply knowledge without repeatedly switching systems or interrupting colleagues.

Microsoft 365 Copilot and Google Gemini support productivity within established ecosystems, while Salesforce Agentforce, ServiceNow Now Assist, and Atlassian Rovo focus on specific business environments. Amazon Q Business provides another option for connecting AI with enterprise information.

Glean takes a broader workplace AI approach by connecting company knowledge across applications and combining search, assistance, and agents. For organizations struggling with information silos and repetitive internal work, this approach offers a way to make existing knowledge more accessible and useful.

The goal of enterprise AI is not simply to give employees another place to ask questions. It is to help them find the information they need, make better use of company knowledge, and move their work forward.