Michael Martino Show

Start with outcomes   There’s a famous line from How Big Things Get Done by Bent Flyvbjerg:  Big projects don’t fail because they’re ambitious. They fail because they’re poorly governed and poorly scoped.    In government, transformation often starts with a solution:  “We need a new case management system.”  “We need AI.”  “We need to modernize.”    That’s activity language. Successful programs st...

Governments are very good at approving transformation but they are much less disciplined at benefiting from it.    If you’re leading a large-scale modernization — digital platform replacement, service transformation, AI implementation, operating model redesign — you need a benefit realization framework that is operational, measurable, and governed.    Start with business outcomes  Most benefit fra...

Start with the business outcome     Before you build anything, define the operational objective. Are you trying to:  Increase first-contact resolution?  Reduce case backlog?  Improve eligibility accuracy?  Shorten processing time?  Lower cost per transaction?    This is not about “using AI.” This is about improving a measurable public-sector performance indicator. If you can’t tie your AI agent to...

Let’s start with a common pattern. An organization says, “We need to improve CX.”     They launch:  a CX initiative  build journey maps  identify pain point   redesign touchpoints.    All this and nothing changes.    Why?    The underlying workflow — the intake process, the routing logic, the approval hierarchy, the eligibility rules, the system architecture — stays the same, and that’s where expe...

 First Contact Resolution isn’t a contact center metric -- it’s a journey outcome. If you try to “train your way” to FCR without fixing the journey, you’ll fail every single time.    Why first contact resolution is misunderstood  Let’s start with the misconception. Most organizations treat First Contact Resolution as a:  frontline performance issue  coaching issue  script compliance problem.    So...

One of the biggest misconceptions is this belief that AI maturity equals removing humans from decisions.    The narrative goes something like this:  “AI will eliminate manual work.”   “AI will replace decision-making.”   “AI will automate the frontline.”    AI reduces repetitive effort but mature AI strategies don’t remove humans. They reposition humans because AI doesn’t replace judgment — it cha...

AI is already operating inside your organization. Your staff are using generative AI tools to draft emails, summarize policy documents, analyze data, and prep briefing notes.    All of this is happening without a coherent, enterprise-level strategy.    Which means decisions about AI are being made:  individually  inconsistently  invisibly    That’s not innovation. That’s unmanaged risk.    An AI s...

Many organizations are building initiatives around activities, projects, and deliverables—instead of anchoring them in clear business outcomes.    If you’ve ever sat in a steering committee where someone says,  “We delivered everything we promised… but the metrics didn’t change,”  this episode is for you.    Activity is not impact  Most organizations don’t actually have a strategy execution proble...

Most government operating models are built around:  programs  policies  channels  functional silos.    Government is organized by what it does and  not by what the customer experiences. As a result, the customer journey is fragmented.    A citizen starts a service in one channel, gets handed off to another team, repeats their story, hits a policy boundary, and eventually gives up—or escalates.   ...

The Illusion of AI readiness  Many governments believe they are AI-ready because they’ve:   published an AI strategy  piloted a chatbot  created an ethics framework  stood up a data or innovation office    All of that is important -- none of it, on its own, equals readiness.    True AI readiness is not about technology adoption--it’s about organizational transformation. AI doesn’t simply automate...

Before we talk about plans, we need to ground the conversation.    An AI agent is not just a chatbot that answers FAQs.    An AI agent is a system that can:  interpret intent  take action across systems  follow defined rules and policies  escalate appropriately  learn within controlled boundaries.    In a government context, that could mean an agent that:  guides a citizen through eligibility, app...

Trust in government services isn’t a “nice to have.”    It’s not a branding exercise.    It’s not a communications problem.    Trust is an operational outcome.    Trust matters   Most people don’t want to interact with government. They interact because they need:  benefits  healthcare  licenses  permits.    Trust determines whether they:  comply willingly or reluctantly  believe the information th...

AI is not a single thing. It’s not one system. It's also not a magic button you bolt onto a broken process.    When most people say “AI,” they’re lumping together:  machine learning  predictive analytics  natural language processing  Generative AI  intelligent automation    Each of these has very different implications for government.    The mistake many agencies make is jumping straight to th...

Most government operating models were not designed for the environment we are operating in today.    They were designed for stability.     They were designed for predictability.    They were designed for policy-driven, siloed execution.    Today’s environment demands something very different:  citizens expect seamless digital services  policy changes are faster and more frequent  funding pressures...

What omnichannel really means   Let’s start by getting clear: Omnichannel isn’t just offering multiple ways to get help.    It’s about offering connected ways.    When someone starts a process on a website, then moves to a chatbot for clarification, gets a follow-up call from an agent, and ends up submitting documents through a mobile app.    The experience should feel like one single conversation...

What Do We Mean by a “Dynamic” Operating Model?  A dynamic operating model has three defining characteristics. It:  separates what must be stable from what must be adaptable  enables rapid reconfiguration of work—not people  is managed as a product, not a one-time design    This means:  Strategy can shift without rewriting job descriptions  New services can be launched without new org charts  Capa...

This isn’t just about technology. It’s about how residents, businesses, service providers, and employees interact with government across every channel—phone, web, email, chat, mobile apps, in-person, kiosks, partner portals—everything.    So, how do you align all those channels into a consistent, intentional experience? That’s where a Channel Experience Roadmap comes in.    Why Channel Planning Ma...

The current landscape   If you’ve ever worked with a worker’s compensation system — whether you’re a case manager, an employer, or a healthcare provider — you know it can be complex.    Paperwork. Phone calls. Forms that look like they haven’t been redesigned since the 1990s. And long waits for updates or approvals.    Over the past decade, many worker’s compensation boards have made large strides...

For most of the last century, healthcare was built around hospitals, clinics, and specialists. You got sick, you went somewhere, and someone took care of you.    But the future? It’s distributed. It’s digital. It’s everywhere.    We’re seeing the rise of virtual care, where patients can consult with doctors from home — and not just for colds or prescriptions. Mental health support, chronic disease...

Today we are going to talk about how governments deliver services, and what the future holds for those delivery channels.    We hear plenty about “digital government,” “online portals,” or “e-services,” but that only tells part of the story. Behind that is a complex ecosystem of channels—web, mobile, call centers, kiosks, in-person offices, even physical mail—and the big question is--how will that...

What we mean by “Digital Government 2.0”  “Digital government 2.0” isn’t just tech procurement. It’s a shift in how government works:  Citizen-centric design — services built around life events: birth, starting school, moving, starting a business, retirement  Shared platforms — identity, payments, notifications, document exchange that any department can plug into  Data as infrastructure — high-qua...

Why cross-functional teams matter  Let’s start with the “why.”    AI projects in government aren’t like rolling out a new app in Silicon Valley. A model that predicts traffic congestion, or flags fraudulent tax claims, or helps prioritize emergency services—these are high-stakes solutions.    If you only put data scientists in a room, you’ll get technically sound models, sure—but they may not alig...

In this episode, we’re going to explore:  Why citizen experience is now the north star for government transformation,  How AI is being used to improve accessibility, responsiveness, and trust, and  What agencies can do right now to start their AI journey responsibly.    The new expectation   Citizens today expect their government to be as responsive as their favorite app.     They want fast, accur...

The Changing Role of Contact Centre Agents  If we rewind 10 or 15 years, the job of a contact centre agent was often about following a script. You answered the call, read from the knowledge base, and handled routine requests.    Today, automation and AI have taken over those routine, repetitive interactions. Customers reset their passwords online. They get status updates through a bot. They pay bi...

For decades, it’s been human agents answering phones, handling emails, and more recently, chat messages. Over time, automation has played a bigger role—IVRs, chatbots, even self-service portals.    With generative AI and agentic AI, we’re seeing something much bigger. These systems aren’t just automating routine tasks—they’re becoming intelligent partners that can support agents in real time, anti...