Nuvepro - Task Intelligence for the Enterprise
Annual ReportQ2 2026 Edition

The State of Task Intelligence 2026

The first annual benchmark on how AI is reshaping work at the task level. Not tool adoption surveys. Not role-level projections. A ground-up analysis of what AI can actually do with each task across every major industry.

Based on 2.1M classified tasks, 894 occupations, 3,126 business workflows, and 81 industries. People Path and Process Path combined.

2.1M

Tasks classified

automate / augment / human-only

722

Occupations scored

across 8 industries

10,000+

Workflows mapped

People Path + Process Path

3.0

Average NTI

Tier 1, Q2 2026 baseline

Task Intelligence: Two Paths

AI readiness is a people problem and a process problem. Task Intelligence covers both.

People Path

Maps every role in the organization into its component tasks. Classifies each task as automate, augment, or human-only. Produces role-level readiness scores, workforce redesign plans, and training prescriptions.

Occupations mapped894
Tasks classified2.1M total
Primary questionWho does what?

Process Path

Maps every business workflow into its step-by-step tasks. Classifies each step as automate, augment, or human-only. Produces workflow redesign plans, automation investment priorities, and integration maps.

Workflows mapped10,000+
Tasks classified17,244 workflow steps
Primary questionWhat happens in the work?

Most AI readiness tools, skills taxonomies, and L&D platforms cover only the People Path. The Process Path is what determines operational ROI. Both are required for a complete picture of where AI creates value in an organization.

Five Key Findings

What the data shows about the state of AI readiness in 2026.

01

25% of all tasks can be automated today

Across 2.1 million classified tasks spanning 894 occupations and 81 industries, 25% can be fully automated with current AI, 50% should be augmented with human-AI collaboration, and 25% must remain human-only. This global split holds remarkably consistent across industries, with manufacturing the outlier at 33% human-only.

02

Task Intelligence covers two paths, not one

Most AI readiness tools measure the People Path: roles, skills, and training gaps. Task Intelligence covers both paths. The People Path maps roles into tasks and classifies each for AI. The Process Path maps business workflows into steps and classifies each for AI. Organizations that only audit roles miss the operational half of the picture.

03

Enterprise AI more than doubles automation potential

Today's AI (Tier 1) produces an average NTI of 2.2 across all industries. Enterprise AI with company-specific data, integrated systems, and trained agents (Tier 3) raises the average to 3.7, a 68% increase. The gap between what generic AI can do and what enterprise AI can do is the actual transformation opportunity.

04

Enterprise SaaS covers 89+ workflows and classifies none for AI

Atlassian and HubSpot alone account for 89 named business workflows spanning 500+ discrete task steps. Neither platform classifies a single task as automate, augment, or human-only. The same pattern holds across Epic, Veeva, Guidewire, Procore, and Toast. Platforms own the workflows. Nobody owns the classification layer.

05

AI adoption is unprecedented, but value extraction requires task intelligence

29% of Fortune 500 are live, paying AI customers within 3.5 years of ChatGPT's launch (a16z, April 2026). But partial automation does not translate linearly to economic value. If AI can automate only 50% of a role's tasks, the remaining tasks become bottlenecks that increase in relative importance. Without task-level classification, organizations cannot identify where value is created, where it is blocked, and where the next dollar of AI investment should go.

The Global Task Split

2.1M tasks classified. This is what the data says about all work.

25%

Automate

Tasks AI handles end-to-end with no human in the loop. Data entry, report generation, transaction processing, code documentation.

50%

Augment

Tasks where human judgment and AI capability combine. Analysis, drafting, decision support, quality control, stakeholder communication.

25%

Human-Only

Tasks requiring full human presence. Clinical care, safety supervision, physical operations, novel judgment, relationship management.

These are Tier 1 (Today's AI) classifications. Enterprise AI with company-specific data and integrated systems (Tier 3) shifts approximately 15% of human-only tasks into augment, and 10% of augment tasks into automate. See the /explore tier toggle to compare Tier 1 vs Tier 3 by industry.

NTI by Industry: Q2 2026

Task Intelligence Index scores. Scale 1.0 (human-only) to 5.0 (fully automatable). Tier 1 baseline.

3.4

Technology

35% auto50% augment15% human

Highest automation potential. AI-generated code and automated testing anchor the score.

112 occupations scored

3.2

Financial Services

31% auto52% augment17% human

High augmentation. Structured data enables AI; regulatory judgment anchors humans.

98 occupations scored

3.1

Retail & E-Commerce

28% auto49% augment23% human

E-commerce drives automation. Physical retail tasks hold the human floor.

76 occupations scored

3.1

Consulting

26% auto56% augment18% human

Highest augmentation rate. Every task benefits from AI; value comes from human judgment on AI output.

64 occupations scored

3.1

Insurance

27% auto53% augment20% human

Document-heavy workflows drive automation. Complex claims keep the human floor elevated.

58 occupations scored

3.0

Healthcare

22% auto55% augment23% human

Most occupations of any industry. Administrative tasks automate; clinical care stays human.

134 occupations scored

2.9

Energy & Utilities

21% auto50% augment29% human

Safety-critical field work limits automation. Remote monitoring is the primary AI opportunity.

72 occupations scored

2.7

Manufacturing

19% auto48% augment33% human

Lowest NTI. Physical tasks dominate. Augmentation, not automation, is the near-term opportunity.

108 occupations scored

The Enterprise AI Gap

Today's AI vs enterprise AI. The difference is the transformation opportunity.

Tier 1: Today's AI

2.2

Average NTI when using generic AI models without company-specific data, policy context, or system integration. This is the baseline for most organizations today.

Tier 3: Enterprise AI

3.7

Average NTI when AI agents have full company context: internal data, integrated systems (ERP, CRM, HRIS), trained on company workflows, and scoped to organizational policies.

The 1.5-point gap is the transformation opportunity

The difference between Tier 1 and Tier 3 (2.2 to 3.7) represents the additional automation potential that becomes available when AI has organizational context. A company at Tier 1 is using AI as a tool. A company at Tier 3 has built AI into its operations. The path between them starts with task classification. You cannot build Tier 3 AI without knowing which tasks it is being built to handle.

The Platform Gap

Enterprise SaaS owns the workflows. Nobody classifies the tasks inside them.

Nuvepro mapped 10,000+ workflows across 1,500+ enterprise platforms and AI vendors. The same pattern appears everywhere: platforms define the process steps, add AI copilots or agents as features, but never classify individual tasks as automate, augment, or human-only. The classification layer is missing in every major platform category.

PlatformWorkflowsTask StepsClassifies for AI?
Atlassian (Jira, JSM, Confluence, Rovo)45~250No
HubSpot (Marketing, Sales, Service, Ops, Commerce)44~260No
Epic Systems (Revenue Cycle, Clinical, Administrative)12~80No
Salesforce / ServiceNow / Workday30~180No
Guidewire / Duck Creek (Insurance)10~60No
Toast / Shopify (Hospitality, Retail)14~90No

ERP / CRM / HCM

SAP, Workday, Salesforce, Oracle

Automate repetitive tasks via workflow rules. No classification layer.

Process Mining

Celonis, UiPath, ServiceNow

Map what processes exist. Do not classify which tasks AI should handle.

Vertical SaaS

Epic, Guidewire, Toast, Veeva

Add AI agents to existing workflows. Classification is left to the customer.

Market Context

What the broader research says about the state of enterprise AI.

29%

of Fortune 500 are live, paying AI customers in 3.5 years

a16z, April 2026

21%

of enterprises meet full AI readiness criteria

Morgan Stanley

74%

of companies cannot keep up with AI skills demand

Josh Bersin

5%

of employees use AI in transformative ways

SHL Research

$5.5T

projected cost of the global skills gap by 2026

IDC

56%

wage premium for workers with demonstrated AI skills

PwC

The pattern across all market research is consistent: enterprise AI adoption is accelerating faster than any prior technology wave. But adoption alone does not produce proportional value. The disconnect is not the quality of the AI models. It is the absence of task-level clarity before deployment. Organizations that start with task classification before tool deployment are the ones closing the AI value gap.

Methodology

How Nuvepro classifies tasks and calculates NTI scores.

Data sources (8 parallel)

  • U.S. Department of Labor occupational data across 894 occupations
  • Real job postings from 2,400+ companies
  • Industry-standard workflow databases
  • Structured task libraries from 4,372 roles
  • AI-generated decomposition, market research, web search, audit history

2.1M classified tasks total.

NTI formula

NTI = (Auto% x 5.0 + Augment% x 3.0 + Human% x 1.0) / 100

Weights reflect degree of AI involvement. Scale: 1.0 (fully human-only) to 5.0 (fully automatable). Published scores use Tier 1 (today's AI). Tier 3 scores are 0.5 to 1.5 points higher.

Classification criteria

Automate signals

Repetitive, rule-based, data-heavy, low ambiguity, structured input/output, no novel situations, measurable success criteria.

Augment signals

Requires context, some judgment, stakeholder interaction, variable input quality, benefits from AI drafting with human review.

Human-only signals

High ambiguity, interpersonal judgment, novel situations, physical presence, accountability and liability, ethical reasoning.

Frequently Asked Questions

Task intelligence is the discipline of mapping, decomposing, and classifying every task in an organization for AI. It covers two paths. The People Path maps roles into their component tasks and classifies each as automate, augment, or human-only. The Process Path maps business workflows into their step-by-step tasks and classifies each the same way. The result is a complete picture of where AI creates value and where human judgment is irreplaceable.
The State of Task Intelligence 2026 draws from Nuvepro's Task Intelligence Database: 2.1M classified tasks across 894 occupations and 81 industries (People Path), plus 10,000+ business workflows across 1,500+ platforms and AI vendors (Process Path). Data sources include U.S. Department of Labor occupational data, real job postings from 2,400+ companies, industry-standard workflow databases, and structured task libraries.
The NTI scores each industry from 1.0 to 5.0 using the formula: (Automate% x 5.0 + Augment% x 3.0 + Human-Only% x 1.0) / 100. A score of 1.0 means tasks are almost entirely human-only. A score of 5.0 means almost entirely automatable. The published scores use Tier 1 (today's AI) classifications. Enterprise AI (Tier 3) scores are 0.5 to 1.5 points higher across all industries.
Tier 1 represents today's generic AI: large language models used without company-specific context, data, or system integration. Tier 3 represents enterprise AI: agents with access to company policies, internal data, integrated systems (ERP, CRM, HRIS), and trained on company-specific workflows. Tier 1 produces an average NTI of 2.2. Tier 3 produces an average NTI of 3.7. The 1.5-point gap is the transformation opportunity that task intelligence unlocks.
Enterprise SaaS platforms own the workflows. They define the steps, enforce the rules, and increasingly add AI copilots and agents. But they do not classify individual tasks as automate, augment, or human-only because that classification requires understanding the organization's specific role mix, human capabilities, risk tolerance, and AI maturity. It is a workforce and operational question, not a software question. That is the gap task intelligence fills.
Andreessen Horowitz found that 29% of Fortune 500 are live, paying AI customers within 3.5 years of ChatGPT's launch. Adoption is not the problem. The problem is that partial automation does not translate linearly to economic value. If AI can do only 50% of a role's tasks, the remaining tasks become bottlenecks that increase in relative importance. Each incremental 1% of AI capability does not equal 1% of economic value. Task intelligence closes this gap by classifying every task before deployment, ensuring AI is applied where it actually creates value, not just where it is easiest to deploy.
The People Path focuses on roles. It asks: for each job in the organization, what are the component tasks, and which can AI handle? This informs workforce planning, training priorities, and role redesign. The Process Path focuses on workflows. It asks: for each business process, what are the steps, and which can AI handle? This informs operational redesign, automation investment, and system integration strategy. Most AI readiness tools cover only the People Path. Nuvepro covers both.
Nuvepro audits every role in a department or business unit, decomposes each role into 15 to 40 tasks, classifies each task using the 8-source methodology, and produces a company-specific NTI. Companies typically find their score differs from the industry average by 0.3 to 0.8 points depending on role mix, technology maturity, and workflow structure. Your team's first AI-enabled task is live in 14 days.

Become an agentic organization.

Task Intelligence is how. Get your company-specific NTI score. Know which tasks to automate, which to redesign with AI, and which to keep human. First AI-enabled task built by your team in 14 days.