Tines Hires Martin Moroney to Turn Internal AI into Everyday Workflows for Customers

New hire aims to make internal AI useful for customers and staff

Tines today said it has appointed Martin Moroney to lead a program focused on internal AI and what the company calls “intelligent workflows at scale.” In plain terms, Tines wants to move beyond one-off automation projects and build systems that let companies use AI inside their daily operations, not just in isolated tools. For customers, the change promises smoother handoffs between people and machines, faster responses to security incidents, and clearer rules for how AI gets used. For Tines, it’s an attempt to translate AI interest into real product features and customer wins that matter in everyday work.

What Moroney will do: setting the playbook for internal AI and scaled workflows

Moroney’s role is both practical and strategic. He will run a “customer zero” strategy, which means Tines itself will be the first user and tester of the new systems. That helps the company discover real problems before rolling solutions out to customers. His remit includes defining how internal AI should act inside companies, designing repeatable workflow templates, and building guardrails so AI behaves predictably.

In practice, this looks like three immediate priorities: helping teams deploy tested AI models inside their operations, turning those deployments into reusable workflow blocks, and creating governance practices so businesses can control risks. The idea is not to chase every new model, but to make AI a steady part of routine tasks—triaging alerts, enriching ticket data, and suggesting next steps—while keeping a human in the loop.

Moroney’s background: the skills that make him a fit

Moroney arrives with a history of building product and operations teams around software that sits at the crossroads of data, automation, and security. He has led initiatives that moved prototypes into production, and he knows how to marry engineering work with clear internal processes. That background matters because turning experiments into company-wide tools is often harder than the initial build: it needs documentation, training, and measurable outcomes. His track record suggests he understands both the technical and organizational work needed to make internal AI stick.

How intelligent workflows at scale could change customer operations

For customers, the promise is concrete. Imagine a security team that gets a suspicious login alert: an intelligent workflow could automatically gather device and user context, run a risk check, suggest action steps, and draft the initial incident report for a human reviewer. That cuts time to resolution and reduces repetitive work.

Beyond security, these systems can route customer service issues, automate compliance checks, or keep internal dashboards up to date. The key change is consistency: instead of one engineer building a custom script, teams get tested workflow modules that behave the same way across the company. That improves speed and predictability, but also makes it easier to audit what the AI did when something goes wrong.

Where this sits in the wider enterprise tech picture

Tines’s move mirrors a broader trend: companies are shifting from flashy AI demos to making AI reliable inside daily tools. Security automation, in particular, has been hungry for ways to use AI to reduce alert fatigue and tighten response times. At the same time, businesses are asking for clearer governance—how decisions are made, who approves them, and how to explain outcomes. Tines is positioning itself at that intersection, where automation vendors compete on ease of use and trust.

What to watch next: milestones, limits and early proof points

In the near term, customers and partners will want to see case studies showing real time saved and errors avoided. Watch for a few early product releases, templates for common workflows, and demonstrations of the company using these tools internally. Risks are real: overly eager automation can break processes, and AI suggestions can be wrong if not properly checked. Success will depend on whether Tines can deliver reusable, well-documented workflows and clear governance tools that reassure IT and security teams.

If Moroney can take prototypes and turn them into repeatable products that teams actually adopt, Tines could make internal AI feel less like risky novelty and more like a tool that helps people do their jobs better. If not, the company will join a long list of vendors that promised big AI gains but left customers juggling pilots without clear outcomes.

Sources

• prnewswire.com