Ashay Kshirsagar, founder of visual production studio Tonic, argues that artificial intelligence strengthens marketing workflows only when teams separate speed from judgment. As 80% of marketers adopt AI for content creation, the industry must decide whether to use the technology to eliminate repetitive tasks or risk replacing cultural awareness with generic output.
AI belongs in the repetitive work
Kshirsagar notes that AI handles tasks teams willingly hand off, such as resizing assets, organizing mood boards, and summarizing briefs. These chores clog up production schedules without adding strategic value.
The problem arises when a polished visual output gets confused with a strong idea. "A lot of business leaders assume that if AI makes something look finished, it has done the hard creative work," Kshirsagar said. "It has only handled the final drawing or rendering, which is not the same as having a good idea."
According to Gartner, 88% of employees with enterprise AI access also use personal AI tools for business tasks to save time. This speed exposes inefficiencies in traditional agency processes, where meetings and endless revisions often masked weak ideas.
Volume does not equal value
A common error among brands is assuming that generating more options increases the likelihood of finding the right answer. AI can produce endless variations, but human judgment determines which concepts deserve to survive.
This distinction matters because a machine cannot read a room or understand why a message succeeds in one city and fails in another. A 2025 Pew Research survey found that 53% of U.S. adults believe AI will worsen people's ability to think creatively.
Kshirsagar points to Tonic's visual work for brands like BMW and Nike as an example. AI-supported production helps teams execute high-quality visual assets at scale, while the creative direction and campaign thinking remain strictly human decisions. Establishing these boundaries is a primary focus for professionals exploring AI for Creatives.
Speed up the start and the end
Kshirsagar separates AI's role into two phases: preparation and production. He advises using the technology for early research and final file organization, but keeping it away from the actual thinking process.
Organizations that apply this discipline see better results. Thomson Reuters' 2025 Future of Professionals report found that companies with visible AI strategies are twice as likely to see revenue growth from AI compared to those using informal approaches.
To maintain control, Kshirsagar advises treating AI output as raw material rather than a final answer. Teams should ask what is wrong with a generated concept and what a braver version would look like, rather than accepting the first decent result.
Why this matters for creatives
The current definition of AI as a collaborative co-pilot is being stress tested. The professionals who will remain indispensable are those who can frame the right problem and understand human behavior, rather than those who simply learn prompt engineering.
"The risk isn't that AI takes jobs, but that we stop training humans to be truly creative," Kshirsagar said.
Creatives must build the habit of forming their own strategic view before consulting a machine. By defending the middle of the creative process, teams can use AI to remove friction without sacrificing the cultural context and taste that make brand work memorable. Teams that want to refine these workflows often look to AI Design Courses to bridge the gap between technical execution and strategic thinking.
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