Despite rapid enterprise adoption of AI-powered marketing tools, campaign execution continues to be slowed by manual production processes, fragmented workflows, and lengthy approval cycles, according to a new report released by Knak, a marketing production platform focused on enterprise teams.

The study shifts attention away from AI-generated content and toward a less visible but increasingly critical stage of modern marketing operations: marketing production. This includes the work required after creative assets are approved, such as building emails, coordinating stakeholders, managing revisions, securing approvals, and preparing campaigns for deployment.

The findings suggest that while AI has accelerated content creation, it has yet to eliminate operational inefficiencies that prevent campaigns from reaching customers on schedule.

Among the report's most notable findings, 85% of surveyed enterprise marketing teams reported missing at least one campaign launch date during the previous 12 months due to workflow-related constraints. Around one in ten organizations said they missed planned launches more than five times annually.

The leading causes were largely operational rather than creative. Nearly half of respondents identified approval and sign-off processes as their biggest source of delays, followed by design production and cross-functional coordination. These results indicate that marketing execution increasingly depends on organizational processes as much as creative excellence.

The report also illustrates the complexity involved in producing what appears to be a routine marketing asset. Creating and launching a single enterprise email campaign frequently requires collaboration among four or more contributors, multiple software applications, and several rounds of revisions before publication.

According to Knak's research, 60% of organizations involve at least four people in producing one email campaign, while 69% require two to three revision cycles before launch. More than half of respondents said they rely on three to five different software platforms throughout the production process, and 51% still manage approvals using email, Slack, or Microsoft Teams conversations instead of centralized workflow systems.

Based on U.S. labor cost estimates referenced in the report, these production activities amount to more than $300 in internal labor for every email campaign before distribution.

The research highlights an important distinction between AI-assisted content generation and production automation. Although 70% of surveyed organizations have introduced AI into marketing production workflows, 88% said AI-generated outputs still require moderate to significant human editing before they are ready for customer-facing campaigns.

Current enterprise AI adoption remains concentrated in creative activities. Nearly two-thirds of respondents use AI to generate first-draft copy, while more than half leverage it for image creation. Only a quarter of organizations currently use AI to build or code emails and landing pages, where much of the production workload remains manual.

This suggests that AI adoption has primarily improved the beginning of the content lifecycle rather than the operational processes that determine campaign speed and execution.

The findings arrive as enterprise organizations continue expanding investments in email marketing, making production efficiency increasingly important. According to the report, email remains the dominant campaign channel, with 88% of respondents producing email marketing assets—well ahead of paid social media, cited by 60% of organizations.

Looking ahead, 52% of enterprise teams plan to increase email marketing investment over the next year, potentially placing additional pressure on production teams unless workflow automation improves.

The report reflects a broader trend across enterprise marketing technology, where organizations are shifting focus from adding AI capabilities toward optimizing operational infrastructure. Many marketing leaders are now evaluating how AI integrates with marketing automation platforms, customer data platforms (CDPs), digital asset management systems, and collaborative production environments rather than viewing generative AI as a standalone productivity solution.

Industry analysts have similarly pointed to operational efficiency as the next phase of AI maturity. Gartner has forecast that organizations will increasingly prioritize AI-enabled workflow automation and process orchestration over isolated generative AI deployments as enterprises seek measurable business outcomes. Meanwhile, McKinsey & Company has reported that companies realizing the greatest value from generative AI typically redesign business processes alongside technology adoption rather than simply introducing new AI tools.

For enterprise marketing teams, the Knak report reinforces that successful AI implementation depends as much on workflow modernization as on content generation. Organizations that streamline approvals, reduce manual handoffs, and integrate production systems may ultimately capture greater value from AI investments than those focused solely on accelerating creative development.

As enterprise MarTech stacks continue to evolve, marketing production is emerging as a strategic discipline rather than an administrative function. AI may accelerate the first draft, but the ability to efficiently move campaigns from concept to launch is increasingly becoming the competitive differentiator.

Market Landscape

Enterprise marketing organizations are increasingly shifting investment from standalone AI content generation toward end-to-end marketing operations. Gartner estimates that marketing organizations continue expanding AI adoption, while workflow automation, process orchestration, and integrated MarTech ecosystems are becoming key priorities for improving operational efficiency. McKinsey research also indicates that organizations generate greater returns from AI when technology implementation is paired with workflow redesign rather than isolated automation initiatives.

Competition across the marketing production space is intensifying as vendors integrate AI with marketing automation platforms, collaboration tools, customer data platforms, and enterprise content operations. Rather than replacing marketers, AI is increasingly being positioned as an accelerator within broader marketing execution workflows.

Strategic Outlook

As enterprise marketing teams increase investments in email marketing and AI-powered content creation, production efficiency is likely to become a key competitive advantage. Vendors that combine AI with workflow automation, collaborative approvals, and seamless integration across enterprise MarTech stacks are expected to play a larger role in helping organizations reduce campaign delays and improve operational agility.

Top Insights

• AI adoption is widespread across enterprise marketing teams, yet 85% still miss campaign launch deadlines because operational workflows remain more challenging than content creation.
• Marketing production has emerged as a strategic discipline, with approvals, revisions, and cross-functional coordination creating greater delays than creative development itself.
• Enterprise email marketing continues expanding, increasing demand for workflow automation that connects AI, collaboration tools, and marketing execution platforms.
• Organizations integrating AI with production workflows rather than standalone content generation are better positioned to improve campaign speed and operational efficiency.
• Marketing leaders are increasingly evaluating production infrastructure as a competitive differentiator within enterprise MarTech ecosystems.

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