AI to lift India's ad volumes up to 18% in 3-5 years as digital and CTV lead growth

AI to lift ad volumes up to 18% in the next 3-5 years - here's how to capture it

AI is no longer a side project. About 42% of advertisers already use it in campaigns, and industry leaders expect total ad volumes to rise up to 18% within the next three to five years, driven by lower costs, wider reach, and better ROI.

Digital will see the strongest lift, followed by connected TV (CTV) and streaming. Smaller and mid-size brands benefit too, thanks to faster creative versioning and higher test velocity.

Where the growth will come from

• Algorithmic buying gets bigger: One major network estimates algorithmically enabled (data-, AI-, or programmatic-driven) spend to grow from roughly 59.5% of total ad spend in 2025 to 79% by 2027.
• CTV and streaming scale: Expect increased volume and better precision as planning and buying workflows get automated.
• Linear TV improves, but stays capped: AI-assisted planning (automated spot selection, reach curves, genre optimization) helps, yet finite inventory limits uplift.
• Performance and retail media lead: Performance channels, retail media networks, and live TV optimization will outpace traditional formats.

Efficiency is the funding model

Reported results show average cost-per-result reductions of 15-20% across markets, with some lower- and mid-funnel cases hitting nearly 50% reductions. That frees budget to reinvest into incremental reach and more experiments.

Agencies are shifting 15-18% of their budgets into automation and AI across trafficking, reporting, performance optimization, and asset versioning. Within digital alone, expect an incremental 6-12% volume uplift over the next 32-36 months.

Who's moving fastest

• Front-runners: BFSI leads adoption through data-rich, performance-driven setups.
• Fast adopters: Auto and D2C lean into AI for faster iteration, audience expansion, and conversion gains.
• High-frequency categories: FMCG and D2C use AI to manage large audiences, creative variations, and always-on cycles.
• Currently contributing via AI: Entertainment/streaming, healthcare, e-commerce, and banking.

What this means for your plan

• Expect 12-18% ad volume uplift over 3-5 years from AI-led efficiencies, better reach, and tighter targeting.
• Plan for 40-50% of the workflow (creative, targeting, optimization, measurement) to be AI-enabled.
• Anticipate 40-70% of planning and buying to be handled through AI tools within five years, subject to regulations.

Practical playbook for marketers

• Audit your baseline: Lock in current CPR/CPA, reach curves, frequency, and test velocity. You need a clear before/after.
• Reallocate budget: Ring-fence 10-20% of spend for algorithmic buying and always-on optimization. Scale what beats your control.
• Increase creative throughput: Build a lightweight system for rapid variants (formats, hooks, CTAs). Target 5-10 active tests per channel per week.
• Go deeper on data: Unify owned/subscribed/syndicated data for audience building and incrementality measurement. Enforce strict quality and consent rules.
• Lean into CTV/streaming: Pilot AI-led planning and frequency control across CTV and AVOD. Tie outcomes to site visits, search lift, or sales where possible.
• Modernize linear planning: Use AI-assisted tools for spot selection and reach optimization to extend incremental reach with capped frequency.
• Retail media now, not later: Test retailer audiences for mid- and lower-funnel impact. Push for clean reporting and path-to-conversion visibility.
• Measurement that moves with you: Combine MMM for planning, MTA where signal allows, and geo-based lift tests for truth checks.
• Upskill the team: Train planners, analysts, and creatives to brief, QA, and iterate with AI. Tooling without skills stalls impact.

What leading agencies are deploying

Examples include AI layers that decode content signals, map behavior, and auto-build channel-agnostic plans, plus automated TV planners that analyze genre, slot, affinity, and reach curves at scale. Others integrate owned, subscribed, and syndicated data into single decisioning systems for faster, sharper optimization.

The point: expect your partners to bring similar stacks. Push them for clear test designs, model transparency, and KPI alignment before scaling.

Governance and guardrails

• Regulations will influence automation rates: Build compliance into briefs, not as an afterthought.
• Brand safety and data rights: Enforce sourcing standards, content filters, and consent frameworks.
• Measurement integrity: Validate AI gains with holdouts, pre/post, and geo-experiments to avoid attribution bias.

For additional context on best practices, see industry guidance such as the IAB's resources on AI for marketing here.

Quick KPIs to track weekly

• Cost per result (by funnel stage) and ROAS
• Incremental reach at frequency caps
• Time-to-creative (brief to launch) and test velocity
• Creative win rate by audience and placement
• Lift metrics: branded search, site visits, geo or cohort-based sales

Bottom line

AI is pushing more volume into the market and squeezing waste out of media. The teams that systematize testing, scale creative variation, and enforce clean measurement will capture the lift. Start with one channel, one KPI, and one tightly designed experiment-then compound the wins.

Level up your team's AI skills: Explore the Marketing Specialist certification to operationalize these workflows here.