exp realty launches AI agents for exp agents

ai: What Mira is and why it matters

exp realty launches AI agents for exp agents with a clear first move: Mira. In 2025 exp announced Mira as an AI-powered business assistant designed to give agents instant business answers at scale. The launch of Mira was unveiled at eXpcon, and agents now have instant visibility into commission status and transaction details. Mira answers questions about commission, transaction milestones, and personalised coaching tips, and it does so via natural language input. As a result, agents spend less time on routine queries, and more time on building relationships and closing deals. This combination makes Mira more than a novelty; it is a practical tool that reduces friction across workflows.

Mira connects to real-time data and systems, and pulls context from multiple sources so agents do not need to switch apps. For example, Mira can surface a transaction deadline, note missing paperwork, and suggest the next steps in minutes. This reduces back-and-forth, and it creates a single point of truth. The point matters because many exp agents work remotely, and they rely on cloud-based tools to manage listings, clients, and leads.

Statistics back the potential. Around 85% of enterprises are expected to have integrated AI agents into core workflows by the end of 2025, which shows how mainstream this approach is becoming (source). Studies also report productivity improvements of up to 40% when AI agents automate repetitive tasks (source). Those numbers explain why exp realty’s move to launch an AI assistant matters to agents who must compete on speed and insight.

Beyond speed, Mira personalises answers. It can highlight which leads to prioritise, suggest messaging, and even prepare a checklist for a listing appointment. That is why brokers and teams can view Mira as both a time-saver and a business co-pilot. For agents who want to grow their businesses, Mira helps free time for high-value work like prospecting and relationship building. The net effect is greater efficiency, and a clearer path to revenue—especially when combined with exp’s revenue share and agent-centric brokerage model.

exp realty exp: How Mira fits eXp’s agent-centred model

exp realty designed Mira to plug into an agent-first philosophy. The company delivered Mira alongside a free ai accelerator series through exp university’s next agent technology training, so agents had both the tool and the training to use it. That combination signals a shift. Rather than simply offering a feature, exp’s platform bundles an ai-powered business assistant with structured education. This helps agents adopt consistent workflows, and it reduces the risk of scattered, ad-hoc use.

Because exp operates as a cloud-based, agent-centric brokerage, Mira supports remote, distributed agents across the network. Mira pulls data from the brokerage’s systems, and it pushes contextual prompts back into the agent’s workflow. In practice, that means agents can get a prompt about a transaction while working in the same platform. The result: less app-switching and fewer missed tasks. This fits exp’s model of scaling best practices across teams and markets.

The launch also reinforced broader strategic moves. exp’s free ai accelerator series and training program show that the company intends to move from tool provider to a platform that combines AI, education, and equity ownership opportunities. For top agents, Mira can act as a personal assistant for daily ops, and for teams it becomes a standardised way to ensure compliance and speed. Leo Pareja and other leaders announced the launch as part of exp university’s next agent technology training, highlighting that agent adoption matters as much as tool capability.

For teams that want to replicate success, exp recommends piloting Mira with a small group and measuring agent productivity and conversion lift. This rollout advice mirrors best practice in other industries, where pilot programs reveal integration gaps and governance needs. If teams track time saved and conversion improvements, they can scale training and expand access across the brokerage. That approach helps maintain quality while enabling rapid agent adoption.

ai-powered crm automation: What Mira automates for agents

Mira focuses on automation that reduces repetitive work inside the CRM. It aims to automate lead scoring and qualification, streamline client follow-ups, schedule appointments, and track transactions. Built to integrate with multiple systems, Mira pulls and pushes data across the broker’s platforms so agents get contextual prompts without switching apps. That design reduces friction and helps agents stay focused on high-value tasks.

Specifically, Mira can score leads based on engagement patterns, then recommend which prospects to call first. It can draft follow-up messages and send reminders by voice or text in English. It can also run document checks and flag missing items in escrow. These functions constitute an ai-powered lead follow-up system and broader workflow automation that real estate professionals need.

When AI agents integrate well with a CRM, they can deliver measurable impact. Reports suggest organisations using AI agents see productivity gains in the order of 30–40% when integrations are properly implemented (source). Those gains include faster lead response, higher lead-to-listing conversion, and shorter time-to-close. For a brokerage on the planet with many remote agents, standardising these automations matters.

To make this practical, exp offered the new crm of choice program and guidance on how to connect tools. This supports teams and brokers who want to adopt Mira alongside legacy systems. For ops teams that handle lots of email and documentation, tools similar to virtualworkforce.ai show how AI agents can automate the lifecycle of transactional messages and reduce handling time automated logistics correspondence. Teams can learn from those workflows to reduce errors and increase response speed, and they can apply the same principles inside a real estate CRM.

streamline help agents: Productivity gains, limits and real risks

AI can streamline many tasks and help agents reclaim time. Organisations that deploy agentic AI often report clear productivity improvements; some studies note up to 40% gains from automation and AI insights (source). That is meaningful for agents who manage many parallel transactions. With Mira, agents can automate follow-up sequences, get pricing signals, and monitor compliance checklists, which reduces manual tracking and error.

However, limits exist. Surveys show that about 90% of organisations face challenges when scaling AI agents, usually due to integration complexity and data management issues (source). Data quality, permissions, and governance are real obstacles. Without clear rules, AI recommendations can be inconsistent or misleading. For that reason, brokers and teams must set guardrails.

Risk controls are straightforward. First, verify sources of recommendations and keep human oversight for pricing and negotiations. Second, set clear data-permission rules so sensitive client information stays secure. Third, log AI actions for auditability and compliance. These steps reduce liability and maintain agent accountability. For broker leaders, appointing internal AI trainers and coaches helps manage adoption and oversight.

Operational teams can also learn from other sectors. For example, virtualworkforce.ai automates the full email lifecycle for ops teams and shows how to ground AI in operational systems like ERP and SharePoint; that approach reduces errors and improves traceability ERP email automation. Applying similar grounding to Mira ensures that recommendations link back to documented data, not guesswork. In short, AI brings clear benefits, but controlled rollout and governance determine whether teams actually capture those productivity gains.

ai accelerator series agents and teams: Training, rollout and coaching

To drive adoption, exp offered an 8-week ai training and a free ai accelerator series that taught agents how to use Mira and other AI tools. The programme, part of exp university’s next agent technology training, combined hands-on labs, playbooks, and live coaching. This training program mattered because tools alone rarely change behaviour; education drives consistent use and embeds best practices.

Rollout advice is simple and practical. Start with a pilot team, and track time saved and conversion changes. Then scale training across teams, measure agent adoption rates, and refine playbooks. For example, pilot teams should log baseline metrics such as lead response time and lead-to-listing conversion. After a defined period, compare the same metrics to show impact on agent productivity and business growth. This iterative approach reduces disruption, and it surfaces required integrations early.

Make AI part of team workflows so agents and teams adopt standard best practice rather than disparate hacks. Appoint AI trainers and coaches to support onboarding, and use recorded sessions for asynchronous learning. Top agents can act as internal champions, and teams should share scripts and templates for follow-up messages and appointment scheduling. That helps scale consistent quality across a large, distributed brokerage.

Finally, link training to tangible outcomes. Measure KPIs like time saved, lead-to-listing conversion, and close speed. For operational learning, teams can consult resources that show how to scale logistics operations without hiring and how to automate emails with Google Workspace and virtualworkforce.ai how to scale logistics operations without hiring and automate logistics emails with Google Workspace. Those resources provide templates for governance, and they show how to define escalation rules that maintain human oversight.

top agents ai trainers and coaches 11 ai trainers and coaches: Next steps for agents and brokers

Top agents should treat Mira as a business co‑pilot, not as a final decision-maker. Use Mira for prospect prioritisation, scripting follow-ups, and quick market checks. Then validate its recommendations before finalising pricing or negotiation strategy. That balance preserves agent judgement while leveraging AI for speed and consistency. Top agents use Mira to automate routine outreach, and they free time to focus on building relationships and closing deals.

For brokers and leaders, appoint internal ai trainers and coaches to support agent adoption. The outline heading uses the phrase “11 ai trainers and coaches”; when planning resourcing, confirm the actual trainer counts from exp materials. Measure KPIs such as agent productivity, lead-to-listing conversion, and close speed. Put governance in place for data access, and document escalation paths so complex issues route to human experts. That approach ensures that AI scales safely across the brokerage.

Brokers should also integrate Mira with the broader tech stack. Use the new crm of choice program to standardise integrations and ensure that data flows across systems. For teams managing many transactional emails, consider systems that automate the full lifecycle of correspondence; those playbooks apply to both logistics and real estate workflows automated logistics correspondence. Use clear training curricula and ongoing coaching so agents learn to use AI thoughtfully and effectively.

Next steps include building an AI blueprint, defining agent adoption KPIs, and creating a roadmap for scaling. Leaders should track agent adoption rates and business growth, and they should reward teams that demonstrate consistent gains. With the right mix of tools, training, and governance, Mira can help agents grow their businesses while maintaining client trust and compliance.

FAQ

What is Mira and when was it launched?

Mira is an AI-powered business assistant that exp realty launched in 2025 to help agents access transaction data and personalised insights quickly. It was unveiled at eXpcon and is part of exp realty’s effort to provide agents with faster answers and standardised workflows.

How does Mira integrate with a CRM?

Mira is designed to pull and push data across the brokerage’s platforms so agents receive contextual prompts without switching applications. This integration reduces manual updates, improves lead follow-up, and helps automate routine CRM tasks.

Does exp provide training to use Mira?

Yes. exp delivered Mira alongside a free ai accelerator series and an 8-week ai training that lives inside exp university’s next agent technology training. The coursework includes hands-on labs, playbooks, and coaching to increase agent adoption.

What tasks can Mira automate for agents?

Mira can automate lead scoring, client follow-ups, appointment scheduling, transaction tracking, and basic document checks. These automations help reduce day-to-day workload and allow agents to focus on building relationships and closing deals.

Are there measurable productivity gains from using AI agents?

Reports indicate organisations see productivity improvements in the 30–40% range when AI agents are properly integrated into workflows (source). The gains depend on data quality, integration, and user adoption.

What are the main risks of deploying AI agents like Mira?

Main risks include integration difficulties, data quality issues, and governance gaps. To control risk, verify sources, keep human oversight for pricing and negotiations, and set clear data-permission rules.

How should brokers measure success after rollout?

Brokers should measure KPIs such as time saved, lead-to-listing conversion, and close speed. Tracking agent adoption rates and business growth helps determine whether the AI and training are delivering value.

Can Mira help remote or cloud-based agents specifically?

Yes. Mira is designed to support cloud-based agents by centralising data and reducing app-switching. It gives agents instant visibility into transactions and helps them manage tasks from any location.

Where can I learn more about operational AI practices that apply to real estate?

Teams can review case studies and operational playbooks such as those that explain how to scale logistics operations with AI agents and how to automate transactional email workflows (source). These resources share governance and integration lessons that apply to real estate.

Who should be involved in an AI rollout at a brokerage?

A successful rollout needs cross-functional involvement: top agents, operations, IT, and appointed ai trainers and coaches. This mix ensures the technology aligns with business goals and that agents receive coaching to use AI as your personal assistant rather than a replacement for judgement.