Tag: ServiceNow

AI operating model: from experimentation to execution in 2026 

Why execution systems, not AI capability, determine enterprise results in an AI operating model 

Most organizations have already experimented with AI. Teams tested copilots, automated small tasks, and explored where models could improve productivity. Those efforts expanded capability, yet execution often remained unchanged. Work still moved through the same bottlenecks. Decisions still slowed in the same places. Outcomes improved in pockets, then plateaued. 

A new phase is taking shape. AI is moving into the flow of work itself. Instead of supporting isolated tasks, it participates in how work is executed across systems, teams, and decisions. 

Agentic AI sits at the center of this shift and is a defining element of the emerging AI operating model. These systems can take action within defined boundaries, execute tasks inside workflows, and coordinate next steps across systems. They extend execution capacity, yet their impact depends entirely on the environment they enter. 

The question facing leaders is clear. If AI is now part of execution, what determines whether it improves outcomes or accelerates existing constraints? 

AI value depends on how work actually moves 

Execution leaders recognize the pattern quickly. Teams deploy capable tools. Early results show promise. Then progress slows. Work becomes uneven. Outcomes vary across teams. 

The issue sits in how work moves through the organization. 

AI operates inside an existing system that includes workflows, decision flow, governance, and human interaction. That system determines how quickly work advances, where it stalls, and how consistently decisions translate into action. 

AI amplifies that system. 

When workflows are fragmented, AI increases the speed of fragmentation. When decision ownership is unclear, AI accelerates inconsistency. When governance is disconnected from execution, risk expands as activity scales. 

When work is structured clearly, the effect changes. AI reduces manual effort, shortens cycle time, and improves consistency across teams. Execution becomes more predictable because decision paths and workflows are already defined. 

This is why many organizations struggle to convert AI investment into measurable value. Capability expands, yet the operating system for execution remains unchanged. 

The operating model becomes the constraint 

An operating model defines how work gets done. It shapes how teams are organized, how decisions move, how governance supports speed, and how people and systems interact during execution. 

Execution leaders feel the impact of operating model constraints every day. Work slows at handoffs. Decisions wait for approval. Teams optimize locally while enterprise outcomes remain inconsistent. AI does not remove these constraints. It exposes them faster. 

Scaling AI requires evolving to an AI operating model that supports faster decision cycles, clearer ownership, and coordinated execution across systems. 

This includes: 

  • Defining decision flow so actions move without unnecessary escalation 
  • Embedding governance into workflows so control does not slow execution 
  • Aligning roles and accountability to human and AI collaboration 
  • Designing workflows that connect systems instead of fragmenting them 

Organizations that address these elements create an environment where AI can contribute to execution. Those that do not continue to absorb delays, inconsistency, and rework at greater speed. 

ServiceNow as a coordination layer for execution 

Enterprise work rarely lives in one system. It spans service platforms, collaboration tools, data environments, and line-of-business applications. Execution breaks down when work moves between these systems without coordination. 

A coordination layer becomes critical. It connects workflows, enforces decision logic, and ensures work progresses across systems with clarity and accountability. 

ServiceNow increasingly serves this role. 

It enables organizations to design workflows that span systems and teams, while embedding intelligence directly into execution. AI can participate in triaging requests, routing work, resolving routine tasks, and supporting decisions within defined workflows. Human judgment remains central, with AI extending execution capacity inside structured processes. 

This changes how work moves. Tasks no longer depend on manual coordination across systems. Decision paths are embedded into workflows. Governance operates within execution instead of sitting outside it. 

The result is coordinated execution at scale. Work advances with fewer interruptions. Decisions translate into action more consistently. Leaders gain greater control without introducing additional friction. 

Where leaders are focusing in 2026 

As organizations prepare for the next phase of enterprise AI, priorities are shifting toward areas where execution, experience, and workflows intersect. 

Accelerating employee productivity with AI agents 

AI agents are taking on repetitive operational work inside enterprise workflows. Service requests, case triage, and routine coordination tasks move faster when AI handles initial steps and escalates where judgment is required. 

Execution leaders focus on reducing manual effort while maintaining control over outcomes. Productivity improves when work flows through defined paths instead of relying on manual intervention. 

Reimagining employee service and onboarding journeys 

Employee experience reflects how work is executed behind the scenes. Onboarding, service delivery, and support processes improve when workflows are coordinated across HR, IT, and service teams. 

AI enables more responsive and adaptive journeys, yet the impact depends on how these workflows are designed. Leaders are redesigning service models so experiences feel consistent and predictable across the organization. 

Embedding AI into everyday workflows 

AI is moving into the systems where work already happens. Employees interact with AI in context, within workflows, rather than through separate interfaces. 

This reduces friction. Decisions happen faster because information, recommendations, and actions are available at the point of execution. Adoption improves because AI becomes part of daily work rather than an additional step. 

Creating clear roadmaps for enterprise AI adoption 

Leaders are moving away from isolated pilots toward structured programs. These roadmaps connect use cases, governance, workflow design, and adoption into a coordinated effort. 

Execution improves when AI initiatives are sequenced, governed, and aligned to outcomes rather than explored independently across teams. 

From experimentation to adoption at scale 

Scaling AI requires more than deploying new capabilities. It requires redesigning how work is executed and how people engage with that work. 

Organizations that succeed treat AI as part of an ongoing evolution toward an AI operating model aligned to enterprise AI strategy and adoption. They design workflows that support human and AI collaboration. They clarify decision ownership. They embed governance into execution. They invest in enablement so teams understand how to work within these new systems. 

Adoption becomes the central factor. 

When teams trust the system, understand their roles, and see how decisions translate into outcomes, new ways of working take hold. Performance improves because behavior changes, not because tools are available. 

Organizations that treat AI as a series of deployments continue to experience uneven results. Use cases succeed in isolation. Scaling remains difficult because the surrounding system has not evolved. 

What to watch at ServiceNow Knowledge 2026 

ServiceNow Knowledge 2026 will highlight how organizations are operationalizing AI within real workflows. 

Key themes include: 

  • AI-powered employee experiences that connect service delivery across functions 
  • Real examples of AI participating in execution within structured workflows 
  • Industry-specific transformations, including complex onboarding environments such as healthcare 
  • Structured approaches to AI strategy that connect experimentation to enterprise programs 

These examples reflect a broader shift. Organizations are moving from capability exploration to execution design. The focus is on how work, decisions, and systems operate together. 

AI success depends on how work is designed 

The next phase of enterprise AI will be defined by execution. 

Organizations that align workflows, decision flow, and governance with AI-enabled execution will move faster and more consistently. Those that do not will continue to experience friction, even as capability expands. 

Agentic AI changes how work can be performed. The AI operating model determines whether that potential translates into outcomes. 

As leaders prepare for ServiceNow Knowledge 2026, the priority becomes clear. Redesign how work moves, how decisions are made, and how teams operate together. When those elements align, AI contributes to execution in a way that scales. 


What is an AI operating model? 

An AI operating model defines how AI agents, workflows, decision flow, and governance work together to execute tasks across the enterprise. It focuses on how work actually moves, ensuring AI supports human judgment within structured processes rather than operating in isolation. 

How is an AI operating model different from traditional AI adoption? 

Traditional AI adoption focuses on deploying tools and capabilities. An AI operating model focuses on how those capabilities are embedded into workflows, decision systems, and governance as part of a broader AI adoption strategy. The difference shows up in execution, where coordinated systems enable consistent outcomes instead of isolated improvements. 

Why do enterprise AI initiatives fail to scale? 

AI initiatives often stall because they are introduced into fragmented workflows and unclear decision systems. Without defined ownership, governance, and workflow alignment, AI amplifies existing inefficiencies. Scaling requires redesigning how work moves, not just expanding AI capability. 

How does an operating model impact AI outcomes? 

The operating model determines how decisions are made, how work flows, and how teams coordinate execution. When these elements are aligned, AI improves speed and consistency. When they are not, delays and inconsistencies increase, limiting the value AI can deliver. 

What role does ServiceNow play in an AI operating model? 

ServiceNow acts as a coordination layer that connects workflows, systems, and decision logic across the enterprise. It enables AI to participate in execution within structured processes, ensuring tasks move consistently while maintaining governance and human oversight. 

What should leaders prioritize in an enterprise AI strategy? 

Leaders should focus on redesigning workflows, clarifying decision ownership, embedding governance into execution, and enabling teams to work effectively with AI. These priorities form the foundation of an effective enterprise AI strategy and adoption approach. Structured programs that connect these elements create the conditions for adoption at scale and sustained performance improvement. 

The $100K cost embedded in a broken physician onboarding process 

Every day a physician is not seeing patients creates about $8,000 in unrealized revenue. Traditional 20-week onboarding cycles delay roughly $100,000+ in revenue per provider before first patient appointments begin. For systems onboarding multiple physicians annually, those delays translate into millions in unrealized revenue. The impact extends to patient access, staff burnout, and recruiting outcomes. 

Healthcare HR teams operate across 30+ disconnected tools, managing manual credentialing processes, fragmented communications, and limited end-to-end status visibility. Physicians face redundant information requests, unclear timelines, and inconsistent requests with unclear ownership from the start. 

A clear separation exists between health systems that modernize onboarding and those that run it manually. Some organizations reach 8- to 12-week onboarding cycles by connecting workflows and shared intake data. Others run 20+ week cycles built on manual processes and providers left waiting on unclear steps and handoffs. 

The hidden costs of a slow physician onboarding process 

Revenue delay gets attention. Operational friction compounds across teams. 

Compliance risk increases when credentialing documentation sits across disconnected tools and inboxes. One missed license verification creates audit risk across every facility and department that touches the record. 

Physician dissatisfaction can start before the first day on site. Candidates comparing offers evaluate onboarding as evidence of how the organization runs day to day. Poor first impressions weaken recruiting credibility and slow future acceptance decisions. 

Operations capacity gets consumed in the background. Administrative burden can exceed 40 hours per hire for capacity-constrained operations teams. Credentialing specialists track down missing documents and confirmations. IT teams work through urgent, last-minute provisioning requests. Practice managers answer recurring status questions. 

Delayed starts extend patient wait times and shift additional load to current clinicians. Every week a physician remains on an unfinished onboarding path, current clinicians absorb additional patient volume, increasing burnout risk and turnover pressure. 

Recruiting pressure rises as faster-moving health systems capture top talent. Your process adds avoidable handoffs and waiting time. 

Read our newest e-book, “Why Physician Onboarding Quietly Undermines Hospital Capacity and Revenue”


FAQs: Hidden costs and risk 

Why does the physician onboarding process take so long? 

Physician onboarding often slows due to manual credentialing, disconnected systems, unclear ownership, and sequential handoffs across HR, IT, and clinical teams. Each delay compounds when work waits for approvals, documents move through email, and progress remains hard to track. 

How does slow physician onboarding affect patient care? 

Delays in the physician onboarding process extend patient wait times and increase demand on existing clinicians. When new physicians start late, current providers absorb additional workload, which strains capacity and raises burnout risk across care teams. 


The four structural changes that improve the physician onboarding process 

Healthcare organizations that reach 8- to 12-week onboarding cycles while strengthening compliance controls and provider experience tend to make four structural changes. These shifts clarify where execution changes first, and they scale because they reduce friction and improve decision flow rather than adding more effort. 

1) Connected workflow coordination reduces system sprawl 

The typical physician gets routed across 30+ disconnected systems during the physician onboarding process. Handoffs add waiting time, and duplicate entry increases rework and dissatisfaction. Manual coordination across HR, credentialing, IT, and practice management teams adds rework and slows decisions. 

Replace fragmented coordination with shared workflow steps and clear ownership. Connect intake, credentialing, and provisioning through shared workflow steps and clear ownership. Reduce or remove duplicate entry by aligning how data moves across systems. 

What changes: Teams run key steps in parallel instead of waiting on serial handoffs. HR completes I-9 verification as credentialing verifies licenses and IT provisions access. The result shows up as shorter cycle time, fewer delays caused by missing information, and less manual coordination. 


FAQs: Workflow coordination 

What is the best way to streamline the physician onboarding process? 

The most effective way to streamline physician onboarding is to connect intake, credentialing, and IT provisioning through shared workflows with clear ownership. Running steps in parallel instead of sequentially reduces waiting time, limits rework, and shortens overall cycle time. 


2) Credentialing workflow design reduces the credentialing bottleneck 

Manual verification of licenses, certifications, and references often adds weeks to the cycle. Documents and confirmations spread across email threads and shared drives. Expiration dates slip when ownership and alerts stay unclear. Physicians do not have a clear view of what remains or where things stand. Credentialing teams lose time that should go to exception handling and quality checks. 

Build credentialing steps that verify, route, and track work consistently. Design credentialing so the record stays complete, tasks move to the right owner, and exceptions surface early. Provide a secure intake experience so physicians submit credentials once, then track progress with current status and clear next steps. 

What changes: Work that used to require back-and-forth often completes in days rather than weeks. Credentialing teams spend more time on quality and exceptions and less time on chasing updates. 


FAQs: Credentialing 

What causes delays in physician credentialing? 

Credentialing delays typically come from manual verification, missing documents, unclear ownership, and lack of visibility into status. When expiration dates, references, and approvals are tracked across emails or spreadsheets, cycle time increases and risk grows. 

How long should the physician credentialing process take? 

Well-structured physician onboarding programs often complete credentialing in weeks rather than months. Cycle time depends on specialty and payer requirements, but consistent workflows and early exception handling significantly reduce unnecessary delays. 


3) Up-to-date visibility enables proactive management 

Many healthcare organizations do not have an easy way to answer key operational questions about their physician onboarding process: 

  • What is the average credentialing cycle time by specialty? 
  • Which handoffs and approvals add the most waiting time? 
  • How does onboarding cycle time correlate with first-year retention? 
  • Where do providers most commonly get stuck? 

Create shared visibility into each provider’s status, ownership, and next required step. Visibility works best when it shows who owns the next action, what remains blocked, and what deadline is at risk. Trend views expose repeated delays in document submission, access provisioning, and start-date readiness. 

What changes: Visibility turns delays into solvable, owned work. Teams spot bottlenecks early enough to rebalance work and clear approvals. Performance trends guide resource allocation. Continuous improvement becomes practical because leaders can see where execution actually slows down. 


FAQs: Visibility and management 

Why is visibility important in the physician onboarding process? 

Visibility allows leaders to see ownership, blockers, and deadlines across onboarding steps. When status and trends remain visible, teams can intervene early, rebalance work, and prevent small delays from turning into missed start dates. 


4) A provider-first onboarding experience reduces friction 

Physicians joining your organization often balance clinical transitions, relocation, and personal logistics. Requirements can stay unclear, forms repeat, status visibility drops, and start dates feel uncertain. That friction becomes part of the physician experience before the first day. 

Design an onboarding experience that shows owners, deadlines, and next steps in one place. Provide contextual help that explains why documents matter and where to find them. Use simple progress indicators. Push updates so physicians receive timely notifications without constant checking. Add guided help and searchable answers for common questions. 

What changes: Clearer onboarding sets expectations for how work gets done. Unclear, inconsistent onboarding creates doubt about day-to-day execution. A provider-first experience reduces administrative inquiries, improves confidence, and supports stronger recruiting outcomes. 


FAQs: Physician experience 

How does onboarding experience affect physician retention? 

The physician onboarding experience shapes early confidence and trust. Clear timelines, fewer administrative burdens, and visible progress reduce frustration and signal how the organization supports clinicians, which influences first-year engagement and retention. 


The business case shows up beyond revenue 

Organizations onboarding 10+ physicians annually often see payback in a matter of weeks through faster time to first patient appointments and recovered operations capacity. 

The impact shows up in revenue, capacity, and retention. 

Revenue impact: Every week you shorten onboarding brings forward about $40,000 in revenue per provider. Cut a 20-week cycle to 10 weeks, and you bring forward about $400,000 in annual revenue per 10 physician starts. 

Operations capacity: Forty hours recovered per physician at $50 per hour equals $2,000 in recovered capacity value per hire. For organizations onboarding 50 physicians annually, that equals $100,000 in recovered operations capacity. 

Retention risk: First-year physician turnover can exceed $500,000 per departure in recruiting, onboarding, and lost productivity. Onboarding experience influences early confidence and commitment, especially when it sets expectations for how the organization supports clinical practice. 

Recruiting advantage: Organizations that share eight-week onboarding timelines in recruiting conversations often see stronger acceptance rates. That advantage compounds in tight talent markets. 


FAQs: Business impact 

How much does a delayed physician onboarding process cost? 

Each week of delay in the physician onboarding process can represent tens of thousands of dollars in unrealized revenue per provider. Delays also increase administrative effort, strain clinician capacity, and raise turnover risk, compounding the financial impact. 


Strategic advantages that scale across hiring waves 

Physician onboarding process speed creates long-term leverage when it improves execution, compliance, and provider confidence. These advantages scale because they reduce rework and clarify ownership across every hire. 

Scale without proportional cost 

Standardized workflows support higher onboarding volume without adding manual coordination. Many teams increase throughput because the process relies less on last-minute triage and more on consistent steps, clear owners, and shared visibility. 

Audit-ready compliance 

Verifications and documents stay tracked with a complete audit trail. Compliance controls strengthen when records remain complete and approvals remain visible. Routine audits become faster to support because the documentation stays connected to the workflow. 

Expand across roles 

A strong onboarding motion scales across advanced practice providers and other clinical roles because the same principles apply. Clear ownership, fewer handoffs, and consistent documentation reduce exceptions and improve predictability. 

Improve using data 

Up-to-date visibility into each provider’s status and next step helps leaders identify recurring delays and redesign the process where it slows down. Investment decisions tied to outcomes become easier because teams can see which changes reduce cycle time and rework. 

What healthcare organizations achieve when they modernize the physician onboarding process 

Healthcare organizations that modernize onboarding see consistent patterns in outcomes. 

  • 30–50% reduction in onboarding cycle time across clinical roles 
  • 50% reduction in credentialing cycle time from submission to approval 
  • 35% reduction in onboarding time for advanced practice providers 
  • Fewer tools needed to complete onboarding steps 
  • Up-to-date visibility into each provider’s status and next step 
  • Audit trails that strengthen compliance controls 
  • Improved provider satisfaction scores tied to clearer onboarding steps 

These results reflect patterns reported by health systems that turned onboarding into a faster, more reliable start process. 

Your path forward 

Over the last five years, our teams have helped healthcare organizations modernize their physician onboarding process. That work clarified where programs stall, what reduces cycle time without increasing risk, and what it takes to sustain adoption across hiring waves. 

Webinar: “The business case for better onboarding” 

See how the shifts work together to reduce delays and accelerate time to first patient appointments. The session connects the four shifts to a practical operating approach and an ROI model based on hiring volume. 

What you will learn 

  • Workflow patterns that reduce credentialing and provisioning delays 
  • How ownership and handoffs affect cycle time across HR, credentialing, and IT 
  • How teams sequence changes to produce early wins and sustain adoption 
  • An ROI model based on hiring volume and current cycle time 

Watch the webinar 

Physician onboarding assessment workshop 

Explore what a faster onboarding program looks like for your organization. The assessment workshop focuses on cycle time, ownership, and adoption so you can decide on next steps with confidence. 

What the assessment workshop covers 

  • Benchmark view: Understand how your cycle time compares across roles and specialties 
  • Process review: Identify the largest sources of waiting time and rework 
  • Systems review: Understand where data and handoffs break across HR, credentialing, and IT 
  • Implementation outline: Define phases, owners, and success measures 
  • A clear next-step plan 

Schedule the assessment workshop 

Delays keep compounding 

Every week of delay creates meaningful productivity and capacity impact. It also gives competitors a head start in attracting top talent. Health systems that streamline the physician onboarding process to eight-week cycles strengthen recruiting credibility, expand clinical capacity sooner, and improve provider confidence early. 

Earlier action brings earlier capacity and a repeatable onboarding motion. Watch the webinar to see how the shifts work together. Use the assessment workshop to identify where your cycle time stalls and what to change first. 


The $2.3 Million Problem Hiding in Your Operations 

We analyzed over 200 mid-market companies and uncovered a consistent pattern: operational friction drains an average of $2.3 million annually from each organization. That loss directly constrains growth investment while faster-moving competitors compound their advantage. 

Mid-market leaders face a clear decision: how long can millions continue leaking from daily operations? 

Where operational inefficiency drains value every day 

Large portions of workforce capacity disappear into automatable tasks. Manual processes inflate operational costs and limit operational efficiency by slowing routine requests far beyond acceptable thresholds. 

Finance teams lose entire workdays each week to low-value administration. Operations leaders wait weeks to approve routine purchases that should move in hours. Procurement absorbs significant effort in administrative work while savings opportunities slip away unnoticed. 

When employees enjoy frictionless consumer experiences but face layered approvals and disconnected systems at work, retention erodes quickly. Replacement costs compound beyond salary alone, while innovation capacity exits with every departure. 


What is operational inefficiency in mid-market organizations?

Operational inefficiency refers to the hidden friction that accumulates across everyday processes, approvals, and handoffs. In mid-market organizations, this often shows up as manual work, disconnected systems, and slow decision-making that quietly increases cost while reducing execution speed and capacity.

Why does operational inefficiency become expensive over time?

Small delays and manual steps compound as organizations grow. Over time, inefficiency spreads across finance, procurement, HR, and operations, creating higher costs, slower execution, and reduced capacity for strategic work.


How mid-market organizations rewire operations with ServiceNow SPM 

Leading organizations rewire how work flows through their operations by adopting ServiceNow Strategic Portfolio Management (SPM) as a foundation for sustained performance gains. 

Across HR, Finance, Procurement, and Facilities, these organizations apply strategic portfolio management to create faster service resolution, higher self-service adoption, and shorter procurement cycles that return time and focus to strategic work. These results create competitive separation that compounds quarter after quarter. 


What is ServiceNow Strategic Portfolio Management (SPM)?

ServiceNow Strategic Portfolio Management (SPM) helps organizations prioritize, fund, and execute the work that delivers the most business value. It connects strategy, investment decisions, and execution so leaders can adjust priorities in real time and reduce waste caused by misaligned initiatives.

How does ServiceNow SPM help reduce operational inefficiency?

ServiceNow SPM improves visibility into demand, capacity, and investment decisions across the enterprise. By aligning work to strategic priorities and streamlining decision flows, organizations reduce manual effort, shorten approval cycles, and eliminate work that does not contribute to measurable outcomes.


Why mid-market ServiceNow transformations accelerate faster than enterprise programs 

Mid-market organizations operate at a unique intersection of scale and agility. Complexity exists, but decision-making remains fast. This combination allows transformation programs to gain momentum quickly when guided by a structured, outcome-driven approach. 

A disciplined ServiceNow consulting approach builds early traction by identifying high-impact friction, redesigning cross-functional workflows, accelerating adoption, and sustaining continuous optimization across the enterprise. 

Early phases establish a unified employee experience foundation. Subsequent stages expand automation, adoption, and cross-functional impact across the organization. 


Why is ServiceNow SPM especially relevant for mid-market organizations?

Mid-market organizations often operate with enterprise-level complexity while retaining faster decision-making and execution speed. ServiceNow SPM brings structure to prioritization and funding without slowing momentum, enabling faster transformation and clearer accountability than traditional approaches.

How is ServiceNow SPM different from traditional portfolio management tools?

Traditional portfolio management tools focus on tracking projects after decisions are made. ServiceNow SPM connects planning, funding, and execution in a single system, enabling continuous prioritization, real-time visibility, and tighter alignment between strategy and operational delivery as conditions change.


See the full path from operational friction to scalable mid-market advantage 

Operational inefficiency rarely announces itself clearly. It hides inside everyday delays, fragmented systems, and manual work that quietly compounds cost. 

Our comprehensive ebook, Rewire Your Business: The Mid-Market Guide to AI-Driven Transformation, explains how mid-market leaders work with ServiceNow SPM implementation partners to convert operational friction into sustained advantage. 

Inside the ebook, you’ll explore how ServiceNow SPM drives impact: 

  • How leading organizations compress procurement cycles and reclaim capacity through a proven ServiceNow SPM transformation framework. 
  • How unified employee experiences reduce attrition risk and improve service performance across HR, IT, Finance, and Procurement. 
  • Where hidden operational costs accumulate and how intelligent automation redirects savings toward growth. 
  • What a structured, milestone-driven transformation journey looks like when execution and value move together. 

Momentum is building across the mid-market with ServiceNow SPM 

Organizations across the mid-market are reshaping operations through ServiceNow SPM partnerships that prioritize flow, speed, and measurable outcomes. As automation expands and expectations rise, operational friction becomes harder to tolerate and more expensive to ignore. 

The complete transformation playbook for reclaiming lost value is waiting.