Author: Justin Lambert

How CIOs and CHROs cut developer ramp time with unified HR–IT orchestration 

Posted on November 21, 2025 by - AI Transformation, Employee Experience (EX)

Every enterprise feels the drag of manual onboarding, but nowhere is the impact sharper than in IT and software development. Engineering teams depend on a dense ecosystem of tools, repositories, environments, and security layers that must be ready on day one. When those systems stay disconnected, onboarding slows, productivity stalls, and visibility disappears across HR, IT, and engineering. 

This installment in our series builds on the foundational narrative introduced in the HRSM overview. It focuses on how intelligent orchestration accelerates onboarding for technical teams and strengthens the connection between HR and IT. 

Technical onboarding requires deeper integration across developer ecosystems. Access must align with engineering roles such as SRE, backend engineer, or platform engineer. Compliance requirements introduce additional complexity. The opportunity is clear: turn onboarding from a manual sequence into an intelligent flow that prepares engineers to build, test, and ship faster. 

Why technical onboarding breaks down 

Technical onboarding introduces challenges that ripple across HR, IT, and engineering, creating friction before work even begins. 

A dense ecosystem of developer tools 

Engineering onboarding involves far more than account activation. Developers need immediate access to repositories, CI/CD pipelines, cloud environments, secrets managers, monitoring tools, and container registries. Each system carries unique permission models and compliance requirements. Manual provisioning turns this into a web of dependencies, repeat requests, and approval bottlenecks. 

The amplified visibility gap 

HR triggers onboarding. IT provisions tools. Engineering managers define role requirements. Yet none of these stakeholders can see onboarding progress in real time. That gap slows sprint planning, blocks code commits, and adds friction to the earliest days of a developer’s experience. 

Productivity friction unique to IT and software 

When a new engineer waits for access, they lose more than time. They lose context. They lose momentum. They lose the confidence that they can contribute quickly. This friction extends across teams as code reviews stall, dependencies wait, and project timelines stretch. 

The fragmentation problem 

Fragmentation across tools, teams, and processes slows engineering productivity and weakens operational flow. 

Fragmentation across the software delivery lifecycle 

A typical engineering environment spans version control, build pipelines, infrastructure provisioning, observability, and deployment systems. Onboarding touches every one of these systems. Without unified orchestration, each step becomes a separate request, a separate approval, and a separate delay. 

Fragmented ownership 

HR manages identity. IT manages provisioning. Engineering manages tool-level permissions. Security manages compliance. Without orchestration linking these responsibilities, onboarding expands from a workflow into a maze. 

Manual work that scales poorly 

Manual provisioning introduces repeated steps: environment setup, key registration, permission alignment, testing access, and more. As organizations scale, these steps multiply. Automation becomes essential. 

The ideal state: orchestrated onboarding across HR, IT, and engineering 

An orchestrated model replaces disconnected tasks with an intelligent, connected flow that accelerates readiness. 

  • One workflow spanning three functions – Orchestrated onboarding connects HRIS, JSM, and developer tools into one intelligent workflow that activates at the moment of hire. 
  • Context-aware, role-based provisioning – Role templates define everything a developer needs based on engineering function. When HR updates a role in the HRIS, JSM immediately orchestrates the provisioning sequence. 
  • Real-time visibility for every stakeholder – HR sees onboarding progress. IT sees provisioning status. Engineering sees when tools are ready so new hires can join sprint work on time. 

Cprime’s solution: intelligent orchestration with JSM for engineering workflows 

Cprime leverages your Atlassian tool stack to redesign onboarding as an integrated, automated workflow that aligns HR, IT, and engineering from the start. 

Unifying HRIS, JSM, and developer tools 

Cprime architects a connected onboarding flow that integrates with systems such as GitHub, GitLab, Jenkins, and cloud IAM. These integrations turn access provisioning into a predictable, automated sequence. 

Turning JSM into the provisioning command center 

JSM becomes the orchestration hub: approvals, provisioning, compliance checks, and communication all move through a single, intelligent workflow. Automation eliminates handoffs and reduces rework. 

Accelerating engineering proficiency 

Atlassian reports that organizations implementing connected, automated onboarding through JSM see engineers reach full proficiency 34% faster. This acceleration comes from fewer delays, cleaner access patterns, and earlier engagement in active development. 

Strengthening security and compliance 

Standardized, role-based provisioning ensures engineers receive the appropriate level of access from the start. Every action is logged, auditable, and aligned with internal controls. 

Business outcomes for CIOs and CHROs 

A unified onboarding model drives measurable impact across productivity, efficiency, and experience. 

  • Faster time-to-productivity – Connected workflows eliminate multi-day waits and allow developers to contribute to active code and infrastructure work much sooner. 
  • Greater operational efficiency – IT handles fewer manual tickets. HR avoids status-tracking overhead. Engineering gains immediate clarity on environment readiness. 
  • Improved developer experience and retention – Developers start contributing earlier and avoid the frustration of stalled onboarding. 
  • Stronger governance – Orchestrated provisioning ensures every access decision is captured, monitored, and aligned with enterprise security standards. 

Why Cprime is uniquely positioned to deliver this 

Cprime brings the expertise, accelerators, and alignment needed to rewire onboarding into an intelligent engineering workflow. 

Cprime brings two decades of Atlassian expertise, proven accelerators for engineering-centric workflows, and a co-design approach that aligns HR, IT, and engineering around one unified experience. As organizations begin transitioning from digital-native to AI-first operations, orchestrated onboarding serves as a strategic foundation for more intelligent, adaptive engineering workflows. 

TBMC 2025 recap: a new era for TBM, value, and the modern operating model 

Posted on November 19, 2025 by - Financial Optimization / TBM / FinOps

TBMC 2025 signaled a turning point for enterprise leaders working to align strategy, spend, and execution. The energy in Miami made one thing unmistakable: TBM is accelerating beyond its roots, and the enterprises driving the most meaningful impact are the ones evolving their operating models around value flow, AI-first execution, and connected financial governance. 

This year’s conference surfaced a unified message across hundreds of conversations, sessions, and forums. Enterprises are moving faster. The pressure for financial clarity is rising. And leaders want a more adaptive, outcome-oriented model for decisions that affect every corner of the business. TBM sits at the center of that shift, and TBM Framework 5.01 emerged as the catalyst. 

Below is a clear view of the themes that shaped TBMC 2025 and what they mean for organizations building toward the next generation of operating discipline. 

TBM Framework 5.01: the most significant update in years 

The headline announcement reverberated across the entire event: TBM Framework 5.01 launches January 1. This update introduces a more modern, accessible, and value-focused version of TBM and reflects the changing demands of enterprise operations. 

The shift is more than cosmetic. Leaders responded strongly to the new emphasis on value drivers rather than data mechanics, a notable realignment that gives organizations a clearer starting point and a faster path to meaningful outcomes. 

Key elements of TBM 5.01 that stood out to attendees 
  • Streamlined certification, replacing outdated programs with a more modern, practical approach. 
  • Practical adoption guidance, including how to start implementing the framework in 30 days—something practitioners have requested for years. 
  • More digestible onboarding materials for new adopters, reducing the learning curve historically required. 
  • Published knowledge artifacts, replacing the tacit, community-driven guidance that previously filled the gaps in documentation. 

These changes significantly lower the barrier for adoption while presenting new opportunities for teams ready to mature into a more sophisticated TBM practice. 

Yet the excitement came with a dose of realism. Many attendees said the pace of change feels fast. As organizations prepare to adopt the new materials, interest in structured learning, advisory support, and TBM-aligned assessments surged. Leaders understand the value of the new framework; now they want a clear roadmap for approaching it with confidence. 

AI-first transformation, enterprise architecture, and value orchestration dominated the event 

While TBM 5.01 was the biggest announcement, the broader conversation revealed deeper shifts in how organizations plan to run. 

AI-first expectations drove the transformation dialogue 

Across sessions and informal discussions, enterprise leaders focused on the same goal: use AI to close execution gaps and bring decision velocity closer to real time. Many described AI as the missing mechanism that links TBM insights to operational change. 

The appetite was strong, but grounded. Leaders want AI applied with purpose, not novelty. They want to accelerate forecasting, strengthen investment choices, and automate the mechanics that slow down strategic execution. 

Enterprise architecture returned to center stage 

EA sessions drew sustained interest across the conference. Leaders are recognizing that enterprise architecture—when paired with TBM and modern portfolio practices—becomes a driver of value flow instead of a gatekeeper. Conversations centered around: 

  • Breaking architecture into clear delivery streams 
  • Integrating architecture earlier in decision cycles 
  • Using EA to modernize platforms and prepare for AI-first operations 

The message landed well: EA is no longer about standards alone. It is part of the machinery of value creation. 

See this in action with the story of a leading international airline that gained the visibility needed to accelerate decisions, reduce friction, and operate with greater strategic confidence. 

Read the case study

Tool-agnostic TBM gained meaningful momentum 

In hallway conversations and booth discussions, a clear trend emerged. Many organizations evaluating TBM practices are moving toward tool-agnostic approaches. Some attendees were not using Apptio at all. Others were exploring more flexible or cost-efficient platforms. The industry is shifting toward TBM as a discipline, not a product. Leaders want adaptability without sacrificing structure. 

Executive alignment remains both critical and challenging 

CFOs and CIOs increasingly share ownership of investment governance, value realization, and performance visibility. Yet many leaders acknowledged ongoing uncertainty about how to activate that partnership inside their operating model. Interest in clearer governance patterns and dynamic funding mechanisms was strong throughout the event. 

The call for real examples was louder than ever 

One theme rose consistently above all others: leaders want to learn from real journeys, not just frameworks. 

Case-based sessions filled quickly. Attendees gravitated toward stories that revealed patterns, mistakes, and practical ways to navigate complexity. 

The appetite for clarity was unmistakable. Organizations want guidance they can act on, rooted in real enterprise behavior, not only theoretical best practices. This reinforces the increasing demand for advisory interaction, working sessions, and diagnostic assessments. 

Cprime’s presence and perspective made an impact 

Cprime’s voice resonated strongly throughout TBMC 2025, and the response validated the central role of the Enterprise Operating Model in powering TBM effectiveness. 

High engagement across our ten sessions 

Our sessions on TBM, enterprise finance, portfolio performance, architecture, and operating model design consistently drew strong attendance. Leaders gravitated toward the intersection of TBM and the operating model: how decisions accelerate when financial governance, architecture, strategy, and delivery operate as a connected system. 

Industry recognition: Apptio’s Americas SPM Partner of the Year 

Cprime received Apptio’s Americas SPM Partner of the Year award, underscoring the measurable value organizations are achieving through our TBM and SPM engagements. The award reflects the momentum behind outcome-based operating model transformation and reinforces our role in shaping the next chapter of this discipline. 

Strong alignment with market needs 

Every conversation we had at TBMC pointed toward the same conclusion: enterprises are ready for a more connected approach to TBM that integrates strategy, financial governance, architecture, portfolio decisions, and AI-first execution into a cohesive operating model. 

What 5.01 means for enterprises moving forward 

TBM 5.01 marks a shift toward simplicity, clarity, and value. The implications for enterprise leaders are significant. 

For organizations beginning their TBM journey: the new guidance accelerates early adoption by providing clearer starting points and structured materials. Teams can apply TBM with greater consistency, confidence, and alignment from day one. 

For maturing practitioners: 5.01 encourages a deeper look at value drivers, costing models, and governance practices. Assessments and maturity analysis will become essential as teams refine how TBM shapes financial and operational decisions. 

For enterprises building AI-first operating models: TBM becomes the economic intelligence layer that powers real-time planning, prioritization, and value flow. AI-first execution demands a clear understanding of how capital, capacity, and outcomes move across the enterprise. TBM strengthens that foundation. 

How Cprime is helping leaders navigate the 5.01 era 

As TBM evolves, enterprises benefit from clear guidance and a structured path that helps them apply the new framework with confidence. We’re helping organizations accelerate momentum through: 

TBM 5.01 learning and enablement: Training and education designed to make the new framework accessible, actionable, and tied directly to enterprise priorities. 

Certification preparedness: Support for teams navigating the modernized certification process and building foundational fluency in TBM 5.01. 

TBM assessments: Diagnostic assessments to evaluate maturity, identify gaps, and highlight the highest-impact areas for improvement, aligned to both 5.01 and Enterprise Operating Model practices. 

Integration into the Enterprise Operating Model: TBM strengthens the connective tissue of the EOM, linking strategy, investment decisions, architecture, and execution. Our operating model solutions help leaders build systems where TBM becomes part of the enterprise’s ongoing rhythm. 

Navigating the next wave of organizational change: insights from the front line 

Posted on November 14, 2025 by - Uncategorized

Every organization is feeling the pressure to adapt faster than ever. Successful transformation demands clarity, commitment, and the right tools, far beyond a simple acknowledgement that change is necessary.  

We brought together a panel of industry leaders for a frank discussion on the challenges and successes of modernizing organizational practices. The conversation spanned topics from shifting mindsets to integrating new technology and revealed key insights for any company preparing for its next stage of evolution. 

The potholes on the road to agility 

A common pain point emerged immediately: the pace of change itself. Many established organizations move too slowly, weighted down by traditional practices and rigid annual cycles. This adherence to old ways often leads to weak prioritization and delayed value, especially when it comes to deciding what work truly matters.  

The real risk lies in prioritizing opinion over economic value. A traditional project-based mentality encourages big, front-loaded expectations with a fixed scope, leaving little room for learning or incremental delivery. This pattern erodes return on investment because much of the potential value surfaces only at the very end of a long project. 

Key challenges highlighted 

The funding shift: Moving from project cost accounting to a product-based operating model is a major financial and cultural hurdle. It requires senior leadership to fund autonomous value streams with an eye toward continuous delivery instead of a single, fixed outcome. 

Mindset and cultural entropy: Getting long-tenured employees to abandon deeply ingrained workflows is challenging. Leaders need to actively support and reinforce the new way of working to prevent teams from reverting to comfortable but ineffective old habits. 

Initial expectations vs. reality: While the promise of Agile is often speed, the immediate gain is usually increased transparency and earlier feedback. Adopting a new framework enables you to deliver valuable increments sooner and surface issues earlier, even when the underlying work remains complex. 

The strategic path to product-centricity 

For organizations committed to making the leap, one team’s transition from an older tool (Planview) to Targetprocess provided a powerful case study.  

A key to their success was acknowledging early that they could not do it alone. Bringing in external partners and coaches added a “new voice in the conversation” and helped accelerate adoption of a structured scaling framework such as SAFe (Scaled Agile Framework).  

A pivotal decision was their shift in focus: they used the migration as an opportunity to re-evaluate their core processes. Instead of configuring a new tool around broken, outdated processes, they first defined how they wanted to work and then configured the platform to support that modern, product-focused methodology.  

The result was rapid deployment of the new system, immediate visibility into data quality issues that had been hidden for years, and, most importantly, the ability to challenge existing norms based on rich, objective data. This new transparency provided a clear line of sight from strategy to execution, helping to eliminate noise and focus capacity on the most valuable work. 

Looking ahead: the AI-powered portfolio 

Looking ahead, AI dominated the conversation. For many organizations, AI investment is a given; the real question is how to manage the corresponding surge in new, complex initiatives. Technology leaders must treat AI as a critical area for portfolio investment and move beyond viewing it as just another cost line. That shift requires leaders to: 

Quantify business value: Accurately measure the financial impact of AI initiatives, whether through cost savings, new revenue streams, or risk reduction. 

Manage the portfolio for innovation: Use the enterprise portfolio tool to track AI investments alongside core product development and ensure alignment with top-level organizational goals. 

Harness AI for the portfolio itself: Use new AI capabilities to analyze portfolio data, predict outcomes, and flag potential bottlenecks so prioritization becomes an informed, data-driven activity rather than a political one. 

Final takeaway: start simple, be tenacious 

For any organization on this journey, the advice from the panel was clear: anchor every decision in a specific business outcome. Be clear on the result you are trying to achieve, invest in the right expertise and tooling with confidence, and approach the work as a marathon that rewards sustained commitment.  

The incremental gains of true agility, transparency, and data-driven decision-making become the foundation for sustainable success. 

How AI-first teams can learn and adapt without waiting

Posted on November 12, 2025 by - Agile & DevOps, AI-Ready Foundations

Agile teams struggle less with reflection itself than with timing. They reflect too late. 

In today’s market, the cost of delayed learning is real: missed deadlines, rising defect rates, burned-out teams, and customer churn hiding in plain sight. 

Most organizations still rely on weekly or biweekly retrospectives as their primary source of insight. That approach is like trying to steer a race car by checking the rearview mirror every few miles. 

But in an AI-native delivery environment, learning shifts from a scheduled event to a continuous system behavior. 

It’s embedded. Continuous. Contextual. 

It is happening right now, whether your team feels ready or not. 

From reflection to orchestration: the shift that changes everything 

We call this shift the “Retrospective Collapse.” It compresses feedback loops from discrete meetings into a state of always-on insight, orchestrated by AI. 

Retrospective Collapse supplements human reflection with real-time, always-available feedback signals that help teams adapt before problems snowball. 

It’s a capability shift powered by Flow-Aware Learning Systems. These are AI-native environments that continuously surface, interpret, and act on delivery intelligence, without waiting for a meeting, a survey, or a formal review. 

What AI-Native Learning Looks Like in Practice 

AI-native teams already deploy AI to accelerate learning across three dimensions: 

1. Blocker Detection Before the Block 
  • LLMs parse communication channels (such as Slack and Jira comments) to detect hesitation, confusion, or duplicate questions. 
  • AI agents flags stories that bounce between swimlanes more than twice and trigger a “pattern of churn” alert. 
  • Sprint dashboards evolve from static charts into real-time friction maps. 
     
2. Real-Time Team Health Signals 
  • Sentiment analysis identifies early signs of burnout or disengagement and feeds insights to Scrum Masters or Agile Coaches automatically. 
  • AI highlights individuals who haven’t contributed to discussions or PRs in several sprints, creating an early flag for morale or bandwidth issues. 
     
3. AI-Augmented Continuous Improvement 
  • Instead of retro notes disappearing into Confluence pages, LLMs convert them into prioritized backlog refinement suggestions. 
  • Delivery metrics combine with NLP-driven qualitative feedback to create coachable moments embedded in the workflow. 
     

These capabilities work within existing tooling by integrating agentic AI into the platforms teams already use. 

Why This Matters Now 

Across AI-native delivery environments, results include: 

  • 18% faster cycle times when AI surfaces blockers mid-sprint 
  • 22% less rework when teams act on continuous insight vs. biweekly feedback 
  • Stronger team satisfaction and velocity scores when improvement opportunities are shared across teams rather than trapped in silos 

When you shorten the time between signal and response, you ship faster, and build smarter, more sustainable teams. 

Your retrospective still matters, but it no longer stands alone. 

The agile ceremony remains essential, and in AI-first teams its role is evolving. 

Retrospectives become moments of synthesis that build on ongoing discovery.  

Learning happens throughout the sprint, not just at the end. 

The next generation of high-performing teams will stand out by how quickly they adapt, because their systems learn with them. 

The real question for every leader: what are your teams still not seeing in time to act? 

From Listening to Leading: Our Journey to TBMC 2025 

Posted on October 29, 2025 by - Enterprise Operating Model, Financial Optimization / TBM / FinOps

Five years ago, we joined TBMC to listen, learn, and share our early perspective. We were a small group of practitioners driven to make technology spending strategic, connecting investments, people, and outcomes through smarter flow. 

Today, at TBMC 2025, that story comes full circle. What started as a few conversations in breakout rooms has evolved into a movement shaped by our clients, our frameworks, and the growth of TBM itself. This year, we return as Platinum Sponsors, hosting 10 sessions and a keynote featuring transformation stories from Southwest Airlines, CNO Financial, and The Standard. 

Shaping the enterprise operating model of the future 

Every one of our sessions this year revolves around a single idea: the modern enterprise operating model, a connected system that aligns strategy, finance, and delivery into a continuous flow of value. From AI-integrated operations and real-time CapEx orchestration to evidence-based management and enterprise finance transformation, we’re showing how TBM is evolving from a cost framework into the performance engine of the modern operating model. 

Whether it’s: 

  • Southwest Airlines reimagining enterprise architecture as the core of agility 
  • BNY Mellon driving evidence-based investment decisions 
  • CNO Financial proving that small starts can scale into enterprise transformation 

Each session and story showcases what’s possible when TBM moves from governance to orchestration. 

From frameworks to living systems 

Our journey mirrors that of our clients, evolving from frameworks and tools into living systems of performance that connect strategy, funding, and delivery into measurable flow. TBM now forms the foundation for adaptive enterprises that learn, evolve, and compete with confidence. 

As we take the stage this year, we celebrate the community that made this evolution real, the clients who transformed TBM theory into enterprise performance, and the shared vision for what comes next: a future where TBM powers every strategic decision across the enterprise. 

Join us at #TBMC25 and see how the next generation of the enterprise operating model is being built, one decision, one connection, and one transformation at a time.  

AI in L&D: enhancing experiences, personalizing training, and improving accessibility 

Posted on October 27, 2025 by - AI-Ready Foundations, Learning

AI brings learning into a new light, reshaping how people learn, grow, and develop across organizations. Learning and development (L&D) is shifting fast, and artificial intelligence (AI) is driving the change. AI now reshapes how people learn, grow, and develop across organizations. From hyper-personalized learning paths to immersive “choose-your-own-adventure” simulations, AI equips L&D teams to build a skilled, engaged, future-ready workforce. 

Rapid technology shifts and changing roles raise the premium on learning and adaptability. Traditional one-size-fits-all training misses the diverse needs of today’s workforce. AI delivers targeted solutions that bring new clarity to how learning connects people and progress, making learning more effective, engaging, and accessible. 

Enhancing the learning experience: beyond the digital textbook 

AI elevates corporate training beyond static decks and lengthy documents. Here’s how: 

AI-powered content creation and curation: 

Generative AI tools can rapidly create a variety of learning materials, from interactive simulations and quizzes to realistic video scenarios. AI also curates up-to-date resources for each learner by scanning large content libraries, saving L&D teams significant time. 

Virtual tutors and AI coaches: 

Always-available virtual tutors support learners 24/7. AI-powered chatbots and mentors provide instant support, answer questions, and guide in the flow of work. These AI companions simulate real-world conversations, deliver performance feedback, and adapt to each learner’s pace. 

Gamification and immersive learning: 

AI adds competition and play to drive engagement. Adaptive challenges, leaderboards, and branching narratives in AI-driven gamification boost engagement and retention. Combined with virtual and augmented reality (VR/AR), AI enables realistic, immersive environments for hands-on training in safe, controlled settings. 

The power of personalization: one size fits one 

L&D aims to deliver truly individualized learning. AI now makes that ambition practical at scale. 

Adaptive learning paths: 

AI-enabled learning management systems (LMS) and learning experience platforms (LXP) analyze data on skills, roles, aspirations, and preferences. AI then constructs unique learning paths and recommends relevant courses, articles, and activities to advance each learner’s goals. 

Identifying and closing knowledge gaps: 

AI excels at identifying subtle patterns and gaps in a learner’s understanding. Intelligent assessments and continuous monitoring pinpoint where an employee needs support and deliver targeted micro-learning in real time. This proactive approach keeps learning relevant and impactful. 

“Choose-your-own-adventure” learning: 

AI-powered branching scenarios and interactive storytelling put learners in the driver’s seat. In these modules, the narrative adapts to each decision, creating engaging, memorable experiences. This approach develops critical thinking, problem solving, and decision-making. 

Accessibility for all: removing barriers to learning 

Real-time translation and transcription: 

For global organizations, AI translates learning content into multiple languages instantly, removing communication barriers. Real-time captioning and transcription in video-based learning improve access for people who are deaf or hard of hearing. 

Text-to-speech and speech-to-text: 

AI-powered text-to-speech converts written content to audio to support learners with visual impairments or reading disabilities. Speech-to-text lets learners dictate responses and interact with platforms by voice. 

Support for neurodiversity: 

AI can be tailored to support neurodiverse learners. For example, it can offer alternative content formats for those with dyslexia and break information into smaller, timed chunks with reminders for learners with ADHD. 

The AI-enabled L&D function: a glimpse into the future 

Integrating AI into learning and training management systems (LMS/TMS) modernizes L&D administration. AI automates course scheduling, learner enrollment, and progress tracking, freeing L&D teams to focus on strategic initiatives. AI-powered analytics reveal program effectiveness and enable data-driven decisions and continuous improvement. 

L&D’s future tracks with the evolution of AI. Expect more sophisticated applications: hyper-personalized learning that adapts in the moment, AI-driven predictive analytics that surface future skills gaps, and seamless integration of learning into daily workflows. 

With AI, L&D teams will evolve from content providers into architects of dynamic, personalized learning ecosystems, illuminating new paths for growth and shining a clearer light on human potential. The goal is to empower employees with the knowledge and skills to thrive in a constantly changing world. The journey has just begun, and the possibilities are limitless. 

How Cprime and Moveworks advance the AI-first employee experience for ServiceNow customers

Posted on October 22, 2025 by - Employee Experience (EX)

Employee expectations are evolving faster than traditional service models can keep pace. Cprime and Moveworks are aligning strengths to accelerate how enterprises deliver intelligent, AI-first support across the digital workplace.

Rewiring employee experience for the AI era

Enterprises everywhere are rethinking how work gets done. Cprime and Moveworks are reshaping how organizations deliver seamless, intelligent support to their people. Cprime brings deep HR Service Delivery (HRSD) and Employee Experience (EX) expertise to integrate Moveworks’ conversational AI within ServiceNow environments, creating a unified solution that scales automation and accelerates service resolution.

Why employee experience needs an AI-first upgrade

Modern employees expect instant, intuitive support. Yet, legacy service desks rely on manual triage and ticket routing. As demand for self-service grows, every delay erodes productivity. The opportunity lies in augmenting ServiceNow with conversational AI that anticipates intent, resolves routine issues autonomously, and frees service teams for higher-value work.

Turning automation into orchestration

The Moveworks platform integrates seamlessly with ServiceNow to deliver measurable value within weeks. Its conversational intelligence enables flexible, multilingual, context-aware interactions that resolve routine requests at scale. Combined with Cprime’s ServiceNow implementation expertise, this integration turns automation into orchestration, aligning technology, teams, and workflows around employee outcomes.

What enterprises gain from the Cprime + Moveworks alignment

Accelerated value: Deploy AI-first support in weeks, not months. Our combined approach streamlines configuration, integration, and adoption so ServiceNow customers realize ROI faster.

Intelligent resolution: Moveworks’ conversational AI resolves Tier 1 requests and delivers proactive insights that elevate ServiceNow performance while reducing manual workload.

Proven expertise: Cprime’s leadership in HRSD and EX ensures every implementation is designed for sustained value, with advisory, integration, and optimization services that scale intelligence across the enterprise.

Looking ahead

The alignment between Cprime, Moveworks, and ServiceNow advances a shared vision for AI-first operations. By embedding intelligence where employees work, organizations accelerate service delivery, improve productivity, and elevate the digital workplace experience. Together, we’re helping enterprises move from automation to intelligent orchestration, where every interaction drives measurable business value.

Why manual onboarding is your hidden HR liability, and how HR Service Management turns it around 

Posted on October 21, 2025 by - Employee Experience (EX)

For many HR teams, onboarding feels less like a strategic milestone and more like a paperwork marathon. New hire forms, email approvals, spreadsheets, and status check-ins consume hours of effort that could be spent engaging new employees. In fact, two in five HR managers who don’t capture onboarding information electronically spend more than three hours per new hire on manual data collection. The cost of inefficiency goes far beyond lost time. It impacts experience, compliance, and retention. 

The hidden price of manual onboarding 

Every extra step, misplaced form, or missed signature introduces friction and error. Up to 25% of HR time is lost to manual data entry and paperwork, and these inefficiencies carry measurable business costs. Studies estimate that turnover costs average 33% of an employee’s annual salary, and poor onboarding is a major contributor. One survey found that 20% of new hires leave within their first 45 days. 

When HR is buried in forms and follow-ups, the human element of onboarding fades. New employees miss critical context, managers lose visibility, and the organization pays for it in attrition and disengagement. 

Why manual onboarding still won’t die 

Despite the clear drawbacks, many organizations still rely on outdated systems. Sixty percent of companies continue to use spreadsheets and email as their primary onboarding workflow tools. This patchwork approach creates invisible bottlenecks: 

  • Fragmented tools and disjointed communication channels. 
  • No single source of truth for tracking onboarding progress. 
  • Limited visibility into what’s done, what’s missing, and who’s responsible. 

When onboarding becomes an improvised process instead of an orchestrated one, small inefficiencies compound into systemic friction. The result is a first-day experience that feels reactive rather than welcoming. 

How HR service management changes the game 

HR Service Management (HRSM) reimagines onboarding as a connected, automated service. It applies structured workflows, defined service levels, and centralized visibility to every stage of the employee journey. In an HRSM model: 

  • AI-powered workflows replace repetitive data entry and predict what’s needed next. 
  • Requests and approvals flow through one digital portal. 
  • AI dashboards surface real-time insights and predict potential bottlenecks. 
  • Intelligent integrations connect HR platforms with IT, facilities, and finance to ensure every detail, from laptop delivery to payroll setup, happens seamlessly. 

Organizations that implement HR automation report significant efficiency gains. One study found that automation can reduce HR administrative work by up to 40%. And when onboarding runs smoothly, new hires are 69% more likely to stay with the company for three years or longer. 

From paperwork to purpose: elevating HR’s role 

Automating onboarding saves time and elevates HR’s role. When paperwork is automated and data flows freely across systems, HR teams can focus on what matters most: designing meaningful employee experiences, supporting culture, and accelerating productivity. 

The benefits ripple outward. New employees reach full productivity faster. Managers gain confidence that every requirement is handled. Leadership sees measurable value in improved retention and reduced cost per hire. And HR reclaims its time for strategy, not spreadsheets. 

The onboarding revolution starts here 

Manual onboarding has become a hidden liability, sapping time, energy, and engagement from HR and new hires alike. Modernizing through HR Service Management brings structure, automation, and insight to the process, turning complexity into clarity. 

The AI-First Service Mandate: 3 Strategic Shifts from the Atlassian Team 25 Europe

Posted on October 14, 2025 by - AI Transformation, AI-Ready Foundations

The Top Shifts: Your Service Mandate from the Conference 

The Atlassian Team 25 Europe conference delivered the definitive blueprint for the AI-First Operating Model. The age of fragmented service is over. With the launch of the Service Collection, Atlassian positions service as a unified, intelligent driver of enterprise advantage, powered by AI. Leaders can recognize and act on these shifts now: 

  • Service is Unified: The wall between external Customer Service (CSM) and internal Employee Service (JSM, HR) has collapsed onto a single platform. 
  • AI is Inherent: Intelligence is built into the foundation of service and functions as the core capability enabling predictive support. 
  • ROI is Immediate: You gain powerful new AI capabilities, Customer Service Management, and Assets for the same price as JSM Cloud alone, maximizing your technology investment. 

Atlassian’s European event underscored a critical shift: service operates as a strategic advantage, not a reactive IT cost center. The new Service Collection advances this vision and signals a unified, intelligent future of service across the enterprise. 

The focus for leaders is now clear: accelerate the transition from siloed support to a single, orchestrated system of service. 

1. The Service Collection: Unifying Experience and Maximizing ROI 

The Service Collection launch demands an immediate evaluation of fragmented service desks. Leaders focused on technology ROI and service resilience gain a strategic advantage: 

  • Service Silos Collapse: Service Silos Collapse: The Collection (JSM, CSM, Assets, Rovo) unifies internal service (JSM) and external service (CSM). The unified flow strengthens feedback loops across Development, IT, and Customer Support.” 
  • Predictive Support Becomes the Standard: With Rovo Agents and built-in AI, the system triages, routes, and fulfills requests automatically. AIOps enhances alert grouping and incident orchestration. Rovo Service for HR delivers AI-powered employee support and automated workflows. This is the foundation of proactive, predictive service. 
  • Maximize ROI with a Free Upgrade: The full Service Collection is available at the JSM Cloud price point. The package adds the CSM app, Assets (now a platform app), and Rovo Agents at no extra cost—creating an opportunity to accelerate value realization by integrating capabilities already included and eliminating redundant point solutions. 

2. Platform Architecture: The Full AI-Native System of Work 

The Service Collection signals a larger shift in Atlassian’s platform architecture. The target: a comprehensive System of Work across the enterprise. AI serves as the foundation for how work gets done: 

  • Unprecedented Cloud Confidence: Cloud migration is supported by Atlassian Ascend, a new program with incentives designed to accelerate and de-risk the transition. New enterprise-grade options like Isolated Cloud and Government Cloud address the most stringent security and compliance needs. 
  • The Three Collections Unite: The Service, Teamwork, and Strategy Collections now operate as one platform. 
  • Teamwork Collection Updates: ‘Create with Rovo’ generates first drafts from an idea. Audio briefings enable on-the-go consumption of Confluence pages. 
  • Strategy Collection Updates: Jira Align, Focus, and Talent add ‘Funds View’ in Focus to track investments and give leaders continuous visibility that keeps work aligned to enterprise goals. ‘Rovo for Strategy’ now provides proactive risk analysis and recommendations.  
  • The Software Collection is now available, including the GA of Rovo Dev, the AI agent for code planning, generation, and review. 
  • AI is Core Architecture: Rovo AI is built into the platform architecture, making intelligence contextual and connected across the stack—ready to accelerate execution and streamline decisions. 

3. Strategic Priorities for Enterprise Leaders 

With AI embedded at the platform level, focus on where intelligence generates the greatest impact across the operating model: 

  1. Lead with an AI Assessment: Quantify your starting point. The AI Assessment evaluates readiness and creates a roadmap to accelerate adoption. 
  1. Accelerate Cloud Migration: The Service Collection is an AI-ready, cloud-only solution. The value—unification, CSM, and AI—drives competitive advantage. Accelerate the move to the modern platform. 
  1. Go Wall-to-Wall with Service: Service Management extends beyond IT. Prioritize unifying employee service (HR, Legal, Facilities) and external service (CSM) to eliminate fragmentation and create shared value. 
  1. Audit for Flow: Identify points in your enterprise operating model where handoffs, approvals, or complex decisions slow momentum. These high-impact areas benefit first from intelligent orchestration. 

Cprime’s Role in What Comes Next: The Path from Vision to Value 

Atlassian has confidently stepped into the AI-native service future. We guide enterprises through this shift with experience and a proven methodology. Our transformation approach clarifies where to begin and converts new platform investments into enterprise momentum. 

We deliver a unified approach across Assessment, Training, and Execution. A package designed to guide enterprise evolution. 

  • Intelligent Assessment: Conduct a strategic assessment to identify friction points and pinpoint where AI delivers the fastest returns. Clarify the starting position and priority moves. 
  • Guided Training & Fluency: Provide focused, private training that drives fluency and successful adoption of new AI-native capabilities. 
  • Embedded Execution: Rewire complex workflows directly into the Service Collection framework. The HRSM solution delivers automated employee experiences that cut onboarding time by up to 98%. 

This guided evolution converts Service Collection capability into enterprise momentum. 

Cprime Welcomes New Leadership to Drive AI-Led Transformation 

Posted on October 11, 2025 by - Company News

Cprime has announced new executive leadership appointments to accelerate its mission of enabling AI-led business transformation across enterprises. These leaders bring deep expertise in technology, operations, and strategic growth—positioning Cprime to drive innovation and measurable outcomes for its clients. 

Expanding Leadership to Strengthen Strategic Vision 

The newly appointed executives will focus on expanding Cprime’s capabilities across its AI Center of Excellence, Enterprise Operating Model practice, and global partner ecosystem. Their collective experience will help clients modernize operations, integrate AI into decision-making, and orchestrate transformation across people, process, and platforms. 

Accelerating AI-Native Transformation 

As organizations shift toward AI-native operating models, Cprime’s leadership team is committed to helping enterprises rethink how work gets done. By combining strategy-first consulting with advanced automation, intelligent analytics, and platform expertise, Cprime enables faster innovation, stronger alignment, and sustainable business growth. 

Commitment to Innovation and Growth 

This leadership expansion underscores Cprime’s commitment to continuous innovation and excellence. With a global footprint and deep partnerships with Atlassian, ServiceNow, IBM/Apptio, and others, Cprime is uniquely positioned to guide organizations through the next era of intelligent orchestration. 

About Cprime 

Cprime helps enterprises bring business into a new light by connecting strategy, execution, and outcomes. Through its blend of consulting, training, and technology enablement, Cprime empowers organizations to operate at the speed of intelligence.