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Understanding the Current State of AI in Businesses

Recent findings from a survey conducted by Harvard Business Review Analytic Services reveal that while a significant majority of companies have transitioned beyond merely experimenting with artificial intelligence (AI), many still fail to harness its full potential effectively. 59% of organizations that currently employ AI are utilizing it in some productive capacity. However, the focus remains largely on incremental improvements aimed at enhancing efficiency and productivity, rather than driving revenue growth.

The study highlights a crucial insight: while companies recognize AI’s role in boosting productivity, its influence on facilitating growth appears to be limited. According to survey respondents, 64% observed significant productivity improvements attributed to AI, while only 30% registered any impact on new revenue streams. The figures reveal a concerning trend — organizations leveraging AI for productivity enhancements prioritize it over developing new business capabilities. This represents a considerable opportunity for companies to rethink their AI implementations and adopt more growth-oriented strategies.

Matt Calkins, CEO of Appian, encapsulates the current dilemma perfectly. He states, "Companies are at a turning point. Instead of predominantly utilizing AI for productivity gains, organizations must shift their focus towards business growth. True AI potential is realized when it evolves from a standalone tool to an embedded workforce asset that supports revenue generation. To achieve this, leaders must prioritize the orchestration of AI systems and establish the necessary frameworks for securely deploying AI in mission-critical environments."

AI: Still Not Fully Embedded in Workflows

The survey reveals that most companies utilize AI as supplementary to their core functions rather than fully embedding it within operational workflows. Only a mere 18% of respondents reported that AI is fundamentally integrated into their business processes. A larger portion, 34%, continues to use AI as standalone tools alongside various processes, while another 34% maintains a hybrid approach, with 12% yet to deploy AI in any workflow.

Despite initial earnings from AI investments, only 16% of participants recognized significant measurable benefits. Most reported their tangible impacts as moderate (33%) or minor (36%), with 8% seeing no measurable value from their initiatives at all. Nonetheless, optimism prevails as 86% of respondents affirm their intent to derive more business value from AI in the future. The transition from early AI results to achieving a noteworthy business impact, however, continues to pose challenges.

The Importance of Workflow Integration

The smooth integration of AI into company workflows is paramount for organizations to realize its full benefit. The respondents indicated that 71% of businesses embedding AI into their processes experienced substantial or moderate benefits. Concurrently, around 76% reported high returns from modernizing legacy systems, 75% from integrating data sources, and 73% from orchestrating processes and workflows across various systems.

A staggering 69% of respondents agreed that legacy systems hinder their ability to scale AI across their organizations, accentuating the urgent need for modernization and better system and data integration. Other noted barriers to embedding AI into workflows included isolated or inadequate data (34%), a lack of integration across systems (31%), and a shortage of AI expertise (30%).

Slower Adoption of AI Agents in Core Areas

The research further uncovers varied levels of AI agent deployment across business functions. Companies actively utilize AI agents in areas such as software development (35%), IT operations (31%), marketing and sales (26%), and customer service (25%). Yet the adoption is notably lower in essential operational sectors like procurement (9%), manufacturing (10%), and supply chain management (11%), which often involve more complex processes demanding higher levels of control and consistency.

To extend AI deployment into these core domains, establishing robust governance structures becomes critical.

Necessity for Robust Guidelines

A striking 92% of respondents recognize that AI agents require established rules to operate securely and effectively. Despite this, less than half (48%) report having defined such guidelines in their organizations. As businesses continue to evaluate agent-based AI (currently used by 25% and considered by 62%), the demand for clearly defined processes will only grow. Without established protocols, AI agents risk unpredictable actions across systems, potentially leading to unintended outcomes.

Redesigning Processes to Unlock AI Value

To fully leverage the capabilities of AI and ensure a sustainable return on investment (ROI), organizations must rethink how they structure and govern their workflows. Significant attention is being directed towards explicitly defining the rules and guidelines that AI must follow (50%), standardizing processes and workflows across functions (49%), and enhancing cross-departmental collaboration (47%)— all aimed at boosting the success of AI implementations.

As Alex Clemente, Managing Director at Harvard Business Review Analytic Services, aptly puts it: "Although businesses are adopting AI, many have yet to integrate it into the core processes essential for their success. Organizations that successfully embed AI within their workflows are better positioned to realize significant value from these technologies."

For in-depth insights and full survey results, you can access the complete study through the provided link.