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Why We’re All In on Auctor

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Auctor, an AI-native system-of-action for systems integrators, officially launched today. As part of its launch, Auctor announced its $20M Series A, with investments from Sequoia Capital (its lead investor), Tercera, HubSpot, Microsoft, OneStream, Workday and a number of other strategic investors.

Auctor has been in stealth mode for a while now, working with early customers to develop an operational backbone for AI-first software implementations. While the company has been quietly building, the platform is already being used by a number of Tercera’s portfolio companies with great results.

A big market, with a big problem

Most people recognize the disruption coming for tech services in the AI era. Work that used to take weeks or months, now takes minutes, and it’s putting real pressure on the age-old time and material model of traditional services. Customers and boards hear what’s possible, and they’re asking partners to do things faster, cheaper and to price less on inputs (hours), and more on outputs (outcomes). At the same time, AI-natives are coming in with big promises, and delivering with fundamentally different economics. It’s the perfect storm.

And yet, this isn’t a death knell for services. In fact, it’s quite the opposite. For those that can adapt to this new way of delivering services, the sky is the limit.

While AI is putting pressure on some service categories, the global IT services market is still expected to grow nearly 9% in 2026 (Gartner). It’s also opening up a range of new opportunities that didn’t exist before. According to Gartner, the AI services market is expected to grow 34% in 2026, and reach $1.11 trillion by 2029. Application implementation, business consulting, and technology consulting are the three fastest growing segments of direct AI services spend. 

According to Gartner, the AI services market is expected to grow 34% in 2026, and reach $1.11 trillion by 2029. Application implementation, business consulting, and technology consulting are the three fastest growing segments of direct AI services spend. 

Source: Gartner, Impacts of AI on IT Services, 2026 Presentation

There are hundreds of thousands of services firms across the globe racing into these segments. Nearly all of them are trying to adopt and embed AI across their own Service Delivery Lifecycle to make themselves “Client Zero” for both survival and customer credibility.

Many of these firms have been successful building their own end-to-end platforms. The GSIs alone have invested millions here. However, the majority of firms simply do not have the time, resources or capability to build from the ground up. Nor are they equipped to continuously refine and manage those platforms as AI evolves.

This is where Auctor comes in. 

A Clear Mandate

Auctor was built to serve these firms. To act as their operational backbone for AI-native software implementations. To embed a firm’s knowledge, workflows, decisions and actions into a living system that accelerates execution from pre-sales through delivery, and compounds value with every project.  

For all the ways that technology has evolved in the last few decades, the way technology is implemented has remained relatively unchanged for decades. Implementation teams rely on a patchwork of meetings, spreadsheets, documents, and tribal knowledge to manage discovery, scoping, solutioning and delivery. Data is fragmented, and decisions and context are scattered across multiple systems and stakeholders. There isn’t a single source of truth. 

That fragmentation leads to misalignment, rework, margin erosion, red projects and missed expectations for both customers and software partners (which are often an implementation firm’s biggest source of leads so highly visible red projects can have significant consequences).

Auctor’s vision is to build on the best foundational LLMs, and finely tune them to SI processes to fix that problem. It’s also highly focused on building in the security, governance and enterprise readiness that will retain and build customer trust – something that matters now more than ever. 

Auctor’s initial focus is squarely on the early stages of software implementations, from pre-sales through discovery and requirements development because that is where the biggest pain is today. But it’s not hard to see that moving into other areas as the platform gets built out and foundational models evolve. 

A Shared Passion

One of the reasons we started Tercera five years ago was because we thought the tech services market was underserved by investors. Our mantra was “services don’t suck”, and our mission was simple – to empower the people who make technology work.

Will and the Auctor team share that same passion for empowering the consultants inside these firms. As Will tells us in his Q&A, they are trying to give these teams a purpose-built platform to help them work faster, with better context and more confidence. A system-of-action so they can focus on the higher-value, more human-centric work. When you talk with Will, that passion is palpable.

Yes this investment might be a bit outside our wheelhouse as a tech services private equity firm. It’s more software than service (service-as-software if you will). We’re coming alongside a number of other strategic investors (although Sequoia is among the best), and it’s super early days for Auctor. But as former operators who have struggled with the specific problem they are trying to solve, and seeing first-hand the  impact it’s making on the companies we’re involved with, it’s kind of a no-brainer. 

Why Auctor is Building the AI System of Action for System Integrators

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A Q&A with Auctor CEO and co-founder, Will Sun


For system integrators, the pressure has never been higher. Clients want faster implementations, clearer accountability, and measurable outcomes. At the same time, delivery teams are being asked to do more with less, adapt to new AI capabilities, and rethink business models built for a different era.

That is the backdrop for Auctor – an AI-native system-of-action designed to give systems integrators an operational backbone that accelerates software implementations and makes each one better than the last. 

Rather than trying to replace SIs, Auctor is building a platform to help them compete in the AI-era. It’s designed to reduce friction and handoffs across the service delivery lifecycle, improving traceability from sales to delivery, and helping firms make that shift toward a more AI-enabled, outcome-oriented model. 

In the conversation below, Auctor’s CEO shares how the company thinks about the services-as-software category, why trust still matters in an AI-driven world, and why system integrators are at the center of AI transformation.

Q: What problem is Auctor trying to solve?

A: Today, buying and implementing enterprise software is far more complicated than it should be. Customers get pulled through a fragmented journey, from initial discovery conversations to pre-sales scoping and requirements development, to the actual implementation, testing and ongoing management of that software. The more critical the software is to enterprise operations, the more people involved – from customer buying committees to software sales and customer success teams, to the SI teams working alongside the customer. All just to realize value from something a customer has already purchased.

Our goal is to simplify that journey and remove the friction between all those handoffs. We want to make the entire experience more seamless so customers can get value from their software as quickly as possible, and SIs can deliver on outcomes faster and with less rework. 

We want to be the single source of truth for the end-to-end customer journey – from the first sales conversation through implementation and post go-live support. For SIs, that matters because so much delivery risk comes from broken context. Information gets lost between pre-sales, SOW creation, requirements gathering, project execution, and customer success. We’re building the connective tissue across all of that.

Q: Why start with system integrators?

A: Today, a purpose-built, AI-native platform for system integrators does not exist. Yet consultants and SIs are the ones doing the work that turns software into business value. They sit at the center of implementation, where complexity, risk, and customer expectations all come together.

If we can help SIs work faster, with better context and more confidence, that has an immediate impact on customer value. If customers get more value, they’ll make future investments in software platforms, consume more features on the platforms, and build deeper partnerships. It’s why software vendors are so excited about what we’re building as well, and why they are investing in us. 

There is this narrative in the market that services and software as we know it are dead. That couldn’t be further from the truth. 

Q: Tell us about the founding story behind Auctor.

A: If you can believe it, the founding of Auctor was actually inspired by Tercera. I’ve always been an entrepreneur and I was spending a lot of time exploring the capabilities of foundation models to understand where the untapped business opportunities were. Through this research I started to dive into the world of SIs, and ran across Tercera. After speaking with the team, I then spent months talking to dozens of system integrators and ISVs across the Tercera 30 to understand how complex software implementations worked, where projects broke down, and where AI could help.

Auctor Founders (from left to right) Matthew Blackburn (CTO), William Sun (CEO), and Sky Ng-Thow-Hing (CPO)

Over time, a pattern became obvious: the workflows were fragmented, the handoffs were painful, and teams were spending too much time recreating context instead of moving projects forward. We developed two features that we thought AI models could automate and tested those with SI leaders. The response was clear: if we built this well, it could fundamentally change how they delivered work.

The rest is history.

Q: What were those two use cases?

A: The first was traceability. Could we give SIs the ability to track every artifact back to its origin? For example, a user story created months into a project can be traced back to the original requirement, the statement of work, and even the pre-sales conversation. That matters enormously for SIs because delivery teams are constantly inheriting decisions made earlier in the cycle. When context is preserved, teams can move faster and with less risk.

The second was building a system-of-action that could take you from the first call through requirements, project plans, SOWs, and ultimately delivery. 

Q: What do you mean by a system of action? What does that mean for SIs?

A: Most traditional enterprise software was designed to be a system-of record or system-of-work. A platform that holds data or facilitates work, but doesn’t proactively help teams move work forward.

A system-of-action actually uses AI to do something with the data that is stored in the system, while still preserving the traceability, observability and governance that is important in these systems.

For SIs, that is critical. You need speed, but you also need trust. Delivery leaders need to understand what the system is doing, why it is doing it, and whether it aligns with what the client expects. That balance between action and accountability is where we think the market is headed.

Q: How are Auctor’s AI agents different from traditional automation?

A: We apply the frontier models in a way that is purpose-built for SI workflows. We are constantly tuning our system for how these LLMs are evolving (which is fast), and are working with hundreds of consultants every day to know what works and what doesn’t. For SIs, that means they can adopt new AI capabilities without taking on all the burden of building, maintaining, and governing those capabilities themselves.

Q: Why wouldn’t SIs just build this on their own?

A: Because staying ahead on AI is hard. The models change constantly, and systems can become outdated every few weeks. It requires a ridiculous amount of time and resources to keep these systems at the forefront of what’s possible, not to mention the security, governance and enterprise readiness factors. It takes a lot to keep these systems reliable and trustworthy for the delivery teams that are staking their reputation on it. Most SIs don’t want to divert resources into chasing the AI stack itself, they want to use it as a building block so they can innovate and stay focused on client value. That is the role we play.

Q: How does Auctor help SIs move toward fixed-fee or new pricing models?

A: First, the platform gives them more confidence in delivery. Teams can work faster, maintain better alignment with clients, and reduce the risk of scope drift or execution surprises. For firms looking to deliver fixed-fee projects with a level of certainty and achieve the required margin on the work, this is important.

Second, it enables firms to rethink staffing models and get more leverage from the team they have. We’ve seen examples where one person can cover work that previously required several roles because the platform helps carry context across project management, solution design, and business analysis tasks. For firms trying to move toward fixed-fee or outcome-based pricing, that kind of leverage is incredibly important.

Q: What excites you most about scaling Auctor?

A: The chance to help modernize an industry that has been overdue for change for a long time.

This is a positive disruption story for system integrators. If we do this right, there will be less waste in the system and greater value delivered. Customers will be happier, partners will see stronger adoption and expansion. That is what excites me most: building something that improves the experience for everyone involved, starting with the firms responsible for making transformation real.

Is shifting to enterprise sales the right move? The answer might surprise you

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Boutique solutions providers often ask me whether transitioning from small or mid-size clients to large enterprise accounts is the key to unlocking step-change revenue growth. The short answer? It depends.

On one hand, enterprise clients come with deeper pockets, greater discretionary spending, and theoretically less risk when it comes to cash collections. It’s also far easier to scale a services organization on the back of large accounts and bigger deals. The rewards can be substantial, especially if the cost of sales remains relatively stable while deal sizes increase.

On the other hand, the road to enterprise sales isn’t always paved with gold. Higher barriers to entry, complex decision-making hierarchies, longer sales cycles, stiffer competition, and stringent certification requirements can make the transition far more demanding than it first appears.

So, is the shift worth it? Let’s break it down.

The Allure of Enterprise Clients

During my early days consulting in Chicago, I was tasked with leading and scaling a small engagement at a Tier-1 telecom provider. At the same time, my close colleague was assigned to a similarly scoped project at a boutique bank. Our Friday night “war room” happy hours quickly became a study in contrasts. She’d regale me with stories of sleek offices, vibrant teams, afternoon wine carts, and a decision-making process refreshingly free of red tape. Meanwhile, I was surrounded by high, beige cubicle walls that smelled faintly of decades old carpet, serenaded daily by the gentle snoring of my cube neighbor, a year shy of retirement. Bureaucratic bottlenecks were more common than afternoon wine breaks.

Fast forward a few years, the irony wasn’t lost on us. That less-than-sexy telecom turned out to be a powerhouse of sustainable growth. This growth fueled our consulting firm’s momentum, generated rich career opportunities, and ultimately helped boost our valuation when the time came to exit. And yes, my friend eventually joined one of my projects at that very same telecom… proving yet again that substance often outlasts sparkle.

For boutique solutions providers, the prospect of landing enterprise clients can feel like a game-changing move. The potential benefits are hard to ignore. These include larger budgets, multi-year contracts, and a steady stream of revenue that provides stability and scalability. Unlike mid-market clients, enterprises often have discretionary funds that enable investment in innovation and strategic initiatives rather than just cost-driven decisions.

Beyond financial advantages, enterprise deals also offer a chance to establish credibility, positioning your firm as an industry leader in the market and with strategic partners. Breaking into this space can unlock repeat business, referrals, and broader visibility in your sector, setting the foundation for sustainable long-term growth.

However, for all its promise, this shift isn’t always a guaranteed golden ticket.

The Hidden Costs and Challenges

What many providers underestimate is the cost and complexity of penetrating the enterprise market. The road isn’t just about selling bigger, it’s about selling differently. Enterprise buyers operate within rigid procurement processes, often requiring multiple layers of approval, risk assessments, and compliance verifications before a deal can move forward.

What many providers underestimate is the cost and complexity of penetrating the enterprise market. The road isn’t just about selling bigger, it’s about selling differently.

Sales cycles stretch longer, sometimes taking months or even years before contracts are signed. Decision-making within large organizations can be bureaucratic, requiring alignment across multiple stakeholders, each with competing priorities and perspectives.

I once led a fast-growing systems integration business with eyes firmly set on a marquee client. We followed the playbook to the letter and hired a well-connected “insider” consultant on retainer, only to watch months roll by with little to show beyond a hefty invoice padded with lavish travel and expense reports.

After a year of patient pursuit, anchored by Account Based Marketing and countless industry expert roundtables, we finally earned our big break: an invitation to join their preferred supplier program. But even this hard-won milestone came with its own maze of challenges. The onboarding process dragged through six more months of dense legal paperwork, spawning a fresh set of workstreams: expanded insurance coverage, newly required certifications such as PMP, ITIL, ISO27001, and more boxes to check than we ever anticipated.

It wasn’t until nearly two years after and a revolving door of sales executives that we started seeing actual proposals. And even then, every opportunity was a battlefield, competing against deeply entrenched incumbents with home-court advantage. We eventually made it to the promised land of active sales and successful delivery. But the victory came at a cost: tight margins at every turn, squeezed by compromises made to gain entry.

Beyond navigating complex decision-making hierarchies, solution providers may need to address significant compliance requirements to take down an enterprise deal, especially deals above $5 million or in highly regulated industries.

Beyond navigating complex decision-making hierarchies, solution providers may need to address significant compliance requirements to take down an enterprise deal, especially deals above $5 million or in highly regulated industries.

Many enterprises won’t even consider vendors unless they meet industry-standard certifications, such as ISO 27001 (for information security), SOC 2 (for SaaS providers), or GDPR/HIPAA compliance (for regulated industries). These certifications require time, financial investment and operational readiness, making them a heavy lift for smaller firms.

Security protocols are another major hurdle. Enterprises demand robust data encryption, controlled access policies, incident response plans, and proactive monitoring to mitigate risks. Without these safeguards in place, boutique providers may struggle to gain entry into enterprise ecosystems, even if they have an exceptional product.

Firms can spend months or even years preparing their infrastructure, security frameworks, and compliance documentation before they can effectively compete in enterprise sales. The investment in the end will likely be worth it — opening up multi-million dollar opportunities and reducing risk for the firm in a time when security threats are only increasing. However, it’s not a small undertaking.

One of the toughest moments in my early career was losing a Fortune 500 client, a blow that still stings. The loss stemmed from employee fraud, a breach that could have been avoided with basic security measures like multi-factor authentication. Ironically, when the client began strengthening their protocols, our direct stakeholder argued for us to be grandfathered in, hoping to sidestep increased costs tied to new vendor requirements. That decision proved costly.

The ex-employee, turned fugitive, had executed a sophisticated scheme, siphoning exactly $1,792 through a cash app. Small theft, big consequences. We didn’t just lose a $10 million annual account. We lost trust. And no recovery effort could fully restore what that breach shattered.

How to Evaluate If the Shift Is Right for You

Before diving into the enterprise space, business leaders need to ask themselves critical questions:

  • Is our offering truly built for enterprise scale? Does your product or service align with the operational complexity and expectations of enterprise clients?
  • Do we have the patience for longer sales cycles? Can your business sustain itself while waiting months for deals to close?
  • Can we meet enterprise requirements? Are your sales, delivery and back-office teams prepared to navigate procurement hurdles, compliance mandates, certification processes, and keep up with best-in-class delivery?
  • Are we willing to invest in enterprise-level relationships? Winning enterprise accounts often means higher-touch engagement, strategic consulting, and ongoing support. Do you have the capacity and capabilities to capture and maintain these relationships?

Enterprise sales can be incredibly rewarding and is increasingly required when you hit a certain plateaus of growth, but only if your business is structured to capitalize on the opportunity effectively. Otherwise, chasing large clients without the right foundation can lead to wasted resources and stagnation instead of growth.

Enterprise sales can be incredibly rewarding and is increasingly required when you hit a certain plateaus of growth, but only if your business is structured to capitalize on the opportunity effectively.

Winning Sales Strategies to Break Into The Enterprise

For those ready to take the leap, navigating this shift requires a strategic approach. Some key tactics include:

  • Build enterprise credibility: Invest in certifications, case studies, and industry partnerships that signal legitimacy.
  • Understand the buying process: Map out procurement steps, approval chains, and key decision-makers to avoid unnecessary bottlenecks.
  • Shorten sales cycles: Develop pilot programs, smaller initial engagements, or bundled offerings to gain traction faster and stick around longer.
  • Strengthen relationship-based selling: Enterprises buy from trusted partners, not vendors. Focus on consultative selling rather than transactional approaches. Make sure you have the right team in sales and service delivery to be that trusted partner.
  • Prepare for post-sale success: Ensure you have the resources to support enterprise customers’ long-term: scalability, customer success teams, and ongoing engagement.

At the heart of the decision lies a single truth: breaking into enterprise sales isn’t just a shift in client size, it’s a transformation in strategy, process, and execution. Done right, it can be the steppingstone to sustainable growth. Done wrong, it can drain time and resources with little to show for it.

So the real question isn’t just “Is enterprise sales the right move?” it’s “Are you prepared to evolve your business to make it work?”

Cathy Jooste is a Tercera Advisor and business leader with nearly 30 years of experience in consultative and technology-enabled services. She excels at scaling companies, optimizing operations, and driving digital transformation. She is the founder of Nuvidea Solutions, and has held executive roles at CGS, Atento, DXC Technologies, Cognizant, Avanade and Accenture.

Why smart year-end planning starts now for Delivery & Ops leaders

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The July – December window can make or break the year for professional services firms. Client budgets tighten, new projects race to signature, and your own consultants begin mapping out well-earned holiday PTO. Waiting until Q4 to reconcile those moving parts is a recipe for margin erosion, last-minute firefighting, and overworked teams. This can be even more acute in smaller firms, which have fewer people to shuffle when things shift.

Investing in a little structured planning will pay off when it matters most. We’ve worked with organizations that have used the checklist below to get ahead of the chaos and the results speak for themselves. With forecast variances consistently under 3% on both a monthly and quarterly basis, these firms were able to predictably manage utilization and revenue forecasting. 

The impact went beyond the numbers: consultants were staffed more strategically, client relationships strengthened, and the internal pressure to “find a home” for bench resources eased significantly. It created a more confident, less reactive culture.

By starting year-end planning six months out, delivery and operations leaders have the runway to fine-tune capacity and set clear expectations with clients before peak demand collides with holiday downtime. The checklist below turns foresight into clear, time-boxed actions so Q4 shifts from seasonal scramble to a more predictable, profitable close.

1. Forecast Resource Needs Early

What to do now:

  • Review Q4 project pipeline and anticipated start dates
  • Build week-by-week supply-vs-demand heat map
  • Identify high-risk projects that could overlap with year-end holidays
  • Flag accounts or deliverables likely to require holiday coverage
  • Assess historical year-end utilization trends for capacity planning
  • Confirm or establish contractor agency relationships in case you need to scale quickly or backfill last-minute gaps

Why it matters:

No one likes scrambling for coverage in December. And sure, looking three to six months ahead can feel early, but even one step forward now saves time, stress, and last-minute headaches later. Thinking through potential gaps now gives you time to fix them calmly, not in a panic. Plus, you’ll catch things like skill mismatches or client patterns that could quietly derail delivery. Getting ahead of this protects revenue and can avoid costly last-minute staffing fixes.

2. Plan Time Off Now

What to do now:

  • Ensure understanding of regional holiday calendars
  • Ask team members to begin thinking about year-end PTO
  • Set a timeline for submitting PTO requests (e.g., by end of Q3)
  • Identify critical roles where staggered leave will be essential

Why it matters:

If you wait too long, everyone wants the same two weeks off, and no one is happy. Getting out ahead of PTO helps you keep projects on track, avoid burnout, and make sure people actually get the break they need. It also helps you avoid needing to pay for contractors or miss revenue targets because you couldn’t deliver what was booked.

3. Develop Preliminary Capacity Plan

What to do now:

  • Estimate Q4 demand based on current backlog and sales pipeline
  • Begin modeling delivery capacity across key teams and geographies
  • Identify potential resourcing gaps based on early PTO signals
  • Explore pulling forward early Q1 work to smooth out resourcing across the holiday period, working with Sales to identify deals that could realistically start sooner
  • Engage in early bench planning and cross-training discussions

Why it matters:

It’s way easier to shift workloads or train backups now than when you’re in the thick of it. You also get a shot at using any idle time more intentionally, before folks get restless or frustrated sitting on the bench. Done right, this improves employee engagement and margin, and helps avoid end-of-year surprises that mess with your financial goals.

4. Engage Clients Early

What to do now:

  • Begin setting expectations around team’s availability
  • Start conversations with larger, strategic clients about their holiday plans
  • Ensure mutual understanding of Q4 project requirements and resource implications 
  • Adjust project plans and milestones based on a realistic view of availability

Why it matters:

Your customers will appreciate the heads-up. If you talk now, you can make smart calls together instead of rushing through decisions when everyone’s out of office and stressed. Focus especially on the larger, more complex projects. These are the ones most likely to slip if planning lags. Doing this sooner rather than later helps you lock in realistic delivery timelines, protect Q4 revenue, and avoid hard-to-recover trust issues when deadlines slip.

5. Align Cross-Functionally

What to do now:

  • Ensure broader delivery team understands the importance of strong planning around Q4 and business impacts
  • Partner with finance to ensure revenue/margin forecasts fully consider holiday impact
  • Partner with sales to align on realistic staffing for late-year deals
  • Sync with HR on leave policy communications, expectations and early consideration around incentivizing teams or individuals who may have high burn projects in Q4
  • Partner with recruiting to get ahead of Q4 hiring needs, especially for roles that are specialized or take longer to fill

Why it matters:

Delivery plans don’t live in a vacuum. If sales is closing late-year deals, finance is forecasting Q4 revenue, and HR is managing PTO and burnout, everyone needs the same view of what’s possible and the potential risks. Getting aligned now helps avoid conflicting priorities, unrealistic asks, and late-stage surprises that can hit margin or delay delivery.

The best Q4s are the ones where you’re not surprised. By planning now, before things get noisy, you can give yourself options: time to shift workloads, loop in clients early, and head off the crunch that usually hits just when everyone’s about to disappear. It’s not just about being prepared; it’s about being in control of how the year ends.

About the co-author

Luke Slevin is the Vice President of Operations at Black Diamond Advisory, a global consultancy in the CPM space and a Tercera portfolio company. Luke has more than 15 years of experience leading delivery and revenue operations, and supporting complex enterprise finance transformations.

AI: Reshaping the future of IT service delivery

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You’ve heard it before: AI has arrived. It’s revolutionizing business. (“OMG, obviously,” as our kids might say.)

But what does that mean for IT services leaders who must juggle near-term business demands while preparing for an AI-enabled future? How do they separate the hype from reality and understand where AI is delivering real value today?

In this article, we discuss practical ways AI is being used today across each phase of the delivery lifecycle today. How forward-looking companies are using a mix of people, AI tools and agents to accelerate the pace of delivery, free up time for delivery teams to do higher level work, and improve adoption.

As former consultants who now work inside software vendors, we offer a unique perspective on how AI is affecting not only our own companies’ product development, but also how it’s influencing the way our service partners leverage and deliver solutions around our products.

AI Across the Service Delivery Life Cycle

It helps to start by thinking of AI as a highly efficient team member. One that is exceptional at repeatable, mundane tasks and infinitely scalable, but still needs oversight. It’s possible today to weave AI-enabled tools and processes across every aspect of the service delivery life cycle (SDLC), from planning through execution and support.

Discovery

Discovery is about fully understanding the scope of a client’s needs. It starts in the sales (or ideation) process, and continues through requirements development. This is when teams alongside clients establish the plan of action, and define features and user stories.

Traditionally, discovery was accomplished manually. Handoffs from sales and delivery were choppy and often incomplete. Delivery teams would then conduct dozens of interviews (in person or long virtual sessions), collect data, map current systems, identify gaps, write requirement documents, and so on. The process relied heavily on human labor. It was time consuming and error prone.

AI can automate much of the tedious grunt work enabling teams to focus on the needs behind the requirements and higher-impact tasks.

Consultants will still manage the overall process and the customer interactions and relationships that are required to do this phase well. However, AI can automate much of the tedious grunt work enabling teams to focus on the needs behind the requirements and higher-impact tasks.

Solution development

This phase entails architecting, developing and building a solution. Traditionally, teams would brainstorm and manually design the architecture. They would interpret business needs and develop diagrams, infrastructure plans, integrations, workflows and proofs-of-concept.

Many delivery teams have already become adept at leveraging existing code or IP to accelerate delivery, but AI can take it a step further, fully automating some of an architect or developer’s day-to-day work.

Many delivery teams have already become adept at leveraging existing code or IP to accelerate delivery, but AI can take it a step further, fully automating some of an architect or developer’s day-to-day work. Popular coding co-pilots, AI-enabled migration utilities, digital business analysts (BAs), and intelligent search capabilities for asset and solution libraries are all tools that solution teams can bring into the mix.

Test & Deploy

In this phase, the solution development team hands the project off to a testing or release-management team. As that team confirms that components of the solution are functioning properly, the code is deployed via continuous integration and continuous delivery (CI/CD) to various environments.

Increasingly, AI can act as the tester and release manager. It can automate deployments, help identify deployment errors and automatically sync environments, all of which results in greater stability and reliability.

Increasingly, AI can act as the tester and release manager.

For example, Copado’s DevOps platform includes products like Robotic Testing, CI/CD, and Value Stream Mapping. VSM can intelligently analyze the cycle time for each phase of SDLC and identify bottlenecks, ultimately enabling the firm to assess whether AI-based process improvements reduced cycle time. It can also guide services firm on DORA metrics (key DevOps metrics measuring speed and reliability). Other more general DevOps vendors like GitHub and GitLab can also play a role in automating deployments to ensure seamless and efficient releases.

Thrive

In the Thrive phase, the solution has gone live in a production environment. During this phase, focus shifts to keeping the solution running smoothly, scaling it effectively, and evolving it based on user needs and business outcomes. This phase is no less critical than the build. In fact, for many organizations, Thrive is where the long-term value of a system is proven or lost.

AI can act as both a watchful system guardian and a continuous improvement coach.

In this phase AI can act as both a watchful system guardian and a continuous improvement coach. Intelligent agents can monitor production environments to proactively detect anomalies, predict outages and recommend optimizations. AI can also be used to develop training and change management plans and documentation to increase and expand system adoption.

And last, but certainly not least, AI can also act as a supplemental customer support and success team. It can assist with customer communications, create knowledge articles or fully handle support issues. More and more, digital agents are able to solve a customer’s query before a case is even logged. If human intervention is required, AI-driven search greatly improves support efficiency.

Accelerating AI Usage within the Delivery Lifecycle

The advent of AI requires a cultural transition, a radical shift in how teams operate. Naturally, this demands change management. Some people are incredibly comfortable with change and will demand these tools to improve performance and stay relevant in their careers. Others may resist them.

Ultimately, it is up to leaders to ensure that the game-changing productivity gains of AI make their way into the organization. Some leaders, like the CEO of Shopify, will mandate it, while others take a lighter touch. Whichever tact you take, the first step is to give the organization encouragement to use these tools, and budget to make them available.

AI agents and tools need to be introduced, trained and continuously developed to address whatever tasks they will undertake, and their performance must be routinely evaluated and adjusted.

AI agents and tools need to be introduced, trained and continuously developed to address whatever tasks they will undertake, and their performance must be routinely evaluated and adjusted.

As these tools and agents are introduced into the flow, governance and measuring success is critical. Delivery leaders should set key performance indicators (KPIs) to help them measure what impact AI is having on teams, customers and overall solution quality to make sure things are improving. Not going the wrong way. Some of these KPIs might be:

  • CSAT (customer satisfaction): How satisfied are customers with our service delivery?
  • Time to value acceleration: How much faster are deployments and solutions delivered?
  • Customer adoption and growth: Is it increasing and/or are more features and projects being started?
  • ESAT (employee satisfaction): How do employees feel about how their jobs are evolving and the quality of the tools we introduce?
  • Talent: Are the tools helping us attract and retain the best talent?
  • Project profitability: Is AI driving delivery cost down and margins up, increasing profitability despite reduced billable hours? Are assets being created and used for repeatable processes?
  • New customer growth: Are we acquiring customers more efficiently?

Next Steps

It’s clear that AI is reshaping how software and systems are being delivered both inside client organizations and services firms. AI offers unprecedented opportunities for efficiency, speed, and customer satisfaction in IT services. If you’re not already thinking about how AI can become more embedded in your SDLC, we can guarantee many of your competitors are.

You can start by working with your teams to think through high-impact use cases. Talk to peers to understand what they are doing, and invest in a few tools with proven AI capabilities in every part of the lifecycle. From there, spend time with teams to understand what’s working and what’s not. AI is evolving so fast that sometimes the best way to learn is to just jump right in, learn and adapt.

About the Authors

Katie Brown and Gloria Ramchandani worked together at Appirio, one of the earliest cloud consultancies known for their high-quality service delivery that could be done far faster, and often at a much lower cost, than traditional service providers. Gloria, currently SVP of product at Copado, consulted with Fortune 100 customers at Appirio and served as product manager of the firm’s DevOps-inspired Cloud Management Center. Katie is the VP of Expert Acceleration at Okta. Previously, she held delivery leadership roles at Appirio, managing solutions, strategic programs, global methodology and operations.

Rethinking global delivery in the age of AI and tariffs

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Over the last two decades, we’ve seen global delivery evolve from a cost-focused initiative to a strategic lever. IT services firms have built centers of excellence offshore, experimented with nearshore models, and found the right mix of skills, price points, and time zones to meet customer demand.

But the playbook is changing. Fast.

Between the rapid advancements in AI and the shifting ground of global trade policies, we’re now navigating a new era — one where IT services firms have to be more agile, thoughtful, and forward-looking about where and how talent is built.

AI Is Changing the Talent Equation

Let’s talk about AI first—because it’s the elephant in every boardroom.

What we’re witnessing isn’t just automation at the edges — it’s a fundamental reshaping of how work gets done across the entire delivery spectrum. AI isn’t just taking on routine back-office tasks anymore, it’s writing code, generating test scripts, drafting documentation and even proposing solution architectures. This is the kind of work that many firms used to assign to junior engineers in offshore teams. Now, AI is doing it in seconds.

All of which is prompting companies to rethink the role of junior talent, the locations they invest in, and the kinds of skills needed to build for the future.

Does this mean companies should shift away from offshore and near shore teams? Not exactly.

What it means is that the profile of the ideal delivery team is changing. Companies are looking for engineers who can co-pilot with AI, not be replaced by it. People who bring contextual understanding, domain knowledge, creativity AND strong technical chops.

Darshan Deshmukh, a Tercera advisor and president of ProcureAbility (a provider of procurement services including advisory, managed services, digital solutions, staffing, and recruiting) said it best: “As organizations focus on the work design aspects of AI, talent with strong critical thinking skills and a high comfort level with change will be essential.”

It’s no longer just about cost arbitrage — it’s about value creation.

This is where nearshore and offshore strategies take on a new importance. What were once hubs tuned for scale and efficiency must now tune for capability and innovation. It’s no longer just about cost arbitrage — it’s about value creation. Nearshore and offshore teams have always been force multipliers, but with AI enablement, they become even more so. Compared to today, tomorrow’s global delivery centers may look leaner, but they will be far more strategic, more productive, and laser-focused on delivering real business impact.

When Politics Meet the Playbook

The overall political dynamic is also forcing businesses to rethink playbooks for global delivery centers (GDCs). Tariffs and barriers to cross-border services, including visa restrictions and digital and data localization laws, have the potential to increase costs over time. If the entire objective for a GDC was purely for lower labor rates and higher margins, just know the math might change.

At the same time, a rise in economic nationalism and isolationist policies across some major markets are prompting companies to reconsider just how “global” their delivery strategies should be. From rising political pressure to repatriate jobs, to new legislation that favors domestic hiring or penalizes offshore spend, companies are navigating not only economic trade-offs but reputational ones.

This doesn’t mean abandoning global teams — but it may shift the calculus on where and how they grow. Countries seen as more politically aligned or economically stable are gaining favor for nearshore and offshore expansion, and delivery leaders are being asked to justify how those teams map not just to cost and skills, but to risk resilience. GDC strategy is no longer just an operational decision. It’s becoming a geopolitical one.

That doesn’t mean the value around having global delivery teams gone. Far from it.

Offshore and nearshore teams continue to be a critical part of the delivery strategy — because of the talent, not just the cost. These regions are home to highly motivated, tech-forward professionals who are hungry to grow and quick to adopt new tools, including AI. Regions like Latin America, Africa, Eastern Europe and India have massive pools of talent that are not only delivery-ready but eager to lead and bring in fresh ideas.

The key is investing in the infrastructure around that talent. Savvy companies are doubling down on training platforms, AI enablement, onboarding programs, and leadership development in these regions — because that’s what turns a capable workforce into a competitive advantage. It’s not just about who you hire or who you partner with in these regions. It’s about how you support them, onboard them into your own processes and (hopefully AI-enabled) systems. It’s about how connected they feel to the customer’s mission.

Savvy companies are doubling down on training platforms, AI enablement, onboarding programs, and leadership development in these regions — because that’s what turns a capable workforce into a competitive advantage.

For example, Zennify – a Tercera portfolio company specializing in data and CX for regulated industries – is finding ways to tap into emerging talent ecosystems like Africa through partnerships. According to CEO Chris Conant, “by prioritizing training, contextual understanding, and collaborative intelligence with AI, we’re not just preparing for the future — we’re actively creating it.”

Advice for Navigating Shifting Terrain

Tariffs and other geopolitical trends may be introducing volatility and change to existing playbooks, but near-term policy shifts shouldn’t fully dictate long-term talent strategy. The firms that win will be the ones who stay committed to nurturing global talent ecosystems — even when it’s not the easiest path.

As delivery leaders, we have to look past the noise and focus on building resilient, future-ready teams. That means balancing risk today while investing in the talent we’ll need tomorrow. Here are a few areas to consider this year:

Re-evaluate your delivery footprint with today’s lens
The assumptions that guided your offshore or nearshore strategy even two years ago may no longer hold. Tariffs, rising service costs, and policy shifts are impacting regions differently — and fast. It’s time to take a fresh look, with an eye on agility, not just rates.

Turn global teams into learning engines
One of the biggest bright spots in all of this? Nearshore and offshore regions are packed with ambitious, capable talent—and they’re often the most enthusiastic adopters of AI tools and new delivery models. In fact, 52% of enrollments in Coursera’s Gen AI classes are from emerging markets. The most successful IT services firms are not just leveraging that—they’re building training frameworks around it. By investing in structured AI enablement and skill acceleration in these regions, you create a flywheel of growth: eager talent, smarter delivery, happier clients.

Plan for uncertainty—because it’s here to stay
Whether it’s a policy shift, a trade rule change or a platform breakthrough, surprises are the new normal. Design flexibility into your resourcing model so you can pivot quickly when the world throws something new at us. Some actions we suggest include developing a multi-region strategy, leaning into a digital workforce culture and reviewing contracts for risk and optionality.

The old model isn’t broken, but it is being rewritten. And as delivery leaders, we have a responsibility to reimagine what great delivery looks like in a world shaped by AI and tariffs.

The world is shifting fast. Make sure you’re moving with it.