New Survey from Harvard Business Review Analytic Services Finds AI Adoption Remains High, Yet Value May Lag Without Modernization and Workflow Integration

Rhea-AI Summary

Appian (NYSE:APPN) sponsored a Harvard Business Review Analytic Services survey (April 29, 2026) showing widespread AI adoption but limited top-line impact. Key findings: 59% have AI in production, 64% report productivity gains, while only 30% see new revenue streams and 16% report high measurable value. The report highlights integration, legacy systems, data quality, and guardrails as primary barriers to scaling AI across workflows.

AI-generated analysis. Not financial advice.

Positive

• 59% of organizations report AI in production
• 64% see productivity improvements from AI
• Embedding AI in processes: 71% report substantial or moderate value
• 76% report strong returns from modernizing legacy systems

Negative

• Only 30% report AI enabling new revenue streams
• Only 16% report a high degree of measurable AI value
• 69% say legacy systems limit AI scaling
• Fewer than 48% have defined rules-based guardrails for AI agents

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A critical AI success gap is emerging for organizations, with 30% surveyed seeing an impact on new revenue streams.

ORLANDO, Fla., April 29, 2026 /PRNewswire/ -- Most organizations have moved beyond experimenting with artificial intelligence, but few are realizing its full value. New research from Harvard Business Review Analytic Services, sponsored by Appian, finds that while 59% of organizations (who are moving forward with AI to some extent) have AI in production, the majority are currently focused on incremental gains that prioritize efficiency and productivity over top-line growth.

Notably, AI has the strongest impact in bolstering productivity, not enabling growth. Respondents indicated that of the AI performance measures their organization tracks, most see impact in productivity improvements (64%) and operational efficiency (58%), while metrics like new revenue streams (30%) and ROI (35%) are among the least likely to have improved. This points to a significant opportunity for organizations to use AI to deliver broader business outcomes and growth.

"Enterprises are at an inflection point. Instead of using AI to drive productivity, organizations must evolve to focus on business growth. That's where Appian comes in," said Matt Calkins, CEO of Appian. "The true potential of AI can only be realized when it moves from a standalone tool to an embedded worker that drives revenue. To get there, leaders must prioritize the foundational orchestration and rules-based guardrails required to safely apply AI to high-impact work."

AI still sits outside the flow of work

In most organizations, AI is being used alongside work, not built into how work gets done, limiting its ability to drive higher-level business outcomes. Only 18% of respondents report that AI is primarily integrated within workflows, while a larger share (34%) continue to use AI as standalone tools alongside processes/workflows, with another 34% reporting a mix of both approaches and 12% not yet using AI in processes/workflows at all.

Most see some returns on AI, but not yet at scale 

Most respondents are seeing some returns from AI investments, but only 16% report realizing a high degree of measurable value. The majority describe the impact as moderate (33%), slight (36%), or have no measurable value (8%). Still, expectations remain high, as 86% agree that their organization is looking to realize more business value from its use of AI. It's clear that AI is delivering some results, but translating those results into meaningful, scalable business impact is proving difficult.

AI delivers value when embedded in workflows

As organizations advance their AI strategies, value is closely tied to how effectively AI is integrated into workflows and applied to operational work. Seventy-one percent of organizations embedding AI into processes realized substantial or moderate value from those efforts, according to respondents. In parallel, approximately three-quarters report strong returns from modernizing legacy infrastructure/systems (76%), integrating data sources (75%), and orchestrating processes/workflows across systems/applications (73%).

Legacy systems continue to limit AI's impact

Nearly seven in ten respondents, 69%, agree that legacy systems are limiting their ability to scale AI across the enterprise. This reinforces the need for modernization and better integration across systems and data. Siloed or low-quality data (34%), a lack of integration across systems (31%), and a lack of AI talent/skills (30%) are also among the most commonly cited barriers to embedding AI into workflows.

AI agent adoption lags in core operations

The research also highlights differences in how AI agents are being applied across the enterprise. Organizations are more actively deploying AI agents in areas such as software development (35%), IT operations (31%), marketing and sales (26%), and customer service (25%). In contrast, agent adoption is more limited in core operational areas such as procurement (9%), manufacturing (10%), and supply chain (11%), where processes tend to be more complex and require greater control and consistency. As organizations look to expand AI into these environments, governance becomes critical.

Most organizations lack the guardrails needed to scale AI agents safely

Ninety-two percent of respondents agree that AI agents need rules-based guardrails to operate safely and effectively, yet fewer than half (48%) agree that their organization has defined such rules (among those at organizations using, considering or exploring agentic AI). As organizations explore agentic AI systems (currently used by 25% of organizations and under consideration by 62%), the need for clearly defined processes and guardrails will become even more critical. Without clear guardrails, agents can act unpredictably across systems, increasing the risk of unintended outcomes.

Process design is emerging as the key to unlocking AI value

Realizing the full value of AI and achieving sustainable ROI requires rethinking how work is structured and governed. According to respondents, organizations are increasingly focused on better defining rules/guardrails that AI must follow (50%), standardizing processes/workflows across functions (49%), and increasing cross-functional coordination (47%) to improve the success of AI implementations.

"Organizations are adopting AI, but many haven't integrated it into the core processes that drive business outcomes," said Alex Clemente, managing director of Harvard Business Review Analytic Services. "Those that successfully embed AI into workflows will be better positioned to realize meaningful value."

Read the full study.

About the Research

In March 2026, Harvard Business Review Analytic Services, sponsored by Appian, surveyed 385 business decision makers from organizations that are exploring, piloting, or actively using artificial intelligence (AI).

About Appian

Appian provides process automation technology. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We've been automating processes for 25 years and understand enterprise operations like no one else. For more information, visit appian.com. [Nasdaq: APPN]

 

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SOURCE Appian

FAQ

How prevalent is AI in production among companies surveyed in the Appian-sponsored HBR study (APPN)?

Direct answer: 59% of organizations reported having AI in production.

Context: According to Appian, most firms use AI for efficiency and productivity rather than for driving new revenue streams or large-scale measurable value.

What barriers did the Harvard Business Review survey identify for scaling AI across enterprises (APPN)?

Direct answer: Legacy systems, poor data quality, lack of integration, and AI skills gaps are top barriers.

Context: According to Appian, 69% cite legacy systems, 34% cite siloed/low-quality data, and 30% cite lack of AI talent as key constraints.

What percentage of organizations reported AI creating new revenue streams in the Appian-sponsored survey (APPN)?

Direct answer: Only 30% of respondents reported an impact on new revenue streams.

Context: According to Appian, organizations more often report productivity or operational efficiency gains than top-line growth from current AI deployments.

How common are rules-based guardrails for AI agents according to the HBR study sponsored by Appian (APPN)?

Direct answer: Fewer than 48% of organizations agree they have defined rules-based guardrails for AI agents.

Context: According to Appian, 92% say guardrails are needed, yet under half report having them, raising governance concerns as agentic AI use grows.

Does embedding AI in workflows affect reported value in the Appian-sponsored HBR survey (APPN)?

Direct answer: Yes—71% embedding AI into processes reported substantial or moderate value.

Context: According to Appian, organizations that modernize infrastructure, integrate data, and orchestrate workflows report stronger returns and higher measurable value.