Road ahead for Programmatic in 2025: An AI-Powered Odyssey – Part 1

In 2025, the fusion of AI and machine learning with programmatic advertising is set to redefine the entire campaign lifecycle – from planning to execution and optimization. As AI algorithms become more sophisticated and machine learning (ML) models continuously evolve, advertisers will gain unprecedented capabilities to hyper-personalize ad targeting, streamline media buying, and achieve real-time optimization.

The rise of AI promises to unlock deeper insights into consumer behaviour, automate decision-making with unparalleled accuracy, and mitigate challenges like ad fraud and ineffective spend. But with these advancements come new considerations, such as balancing privacy regulations and data ethics with innovation.

This two-part feature explores how AI-driven automation will shape the future of programmatic advertising, giving marketers an edge in efficiency, effectiveness, and ROI in the coming year.

The AI revolution

Programmatic advertising is on the cusp of a transformative phase in 2025, powered by advancements in AI, machine learning, and privacy-centric technologies, says Vasuta Agarwal, Chief Business Officer, Consumer and Performance Advertising, InMobi.

“At InMobi, we are leading this evolution with solutions that enhance efficiency and redefine how brands connect with their audiences. AI and ML are set to revolutionize the programmatic space by enabling hyper-personalized targeting, bidding strategies, delivering campaigns tailored to individual preferences through AI-driven insights. These technologies also bring real-time supply optimization, maximizing inventory usage by analysing demand and supply patterns, and dynamic pricing models that adjust strategies for cost-effectiveness while achieving campaign goals. With the rapid pace of AI innovation, new tools and capabilities are emerging continuously, ensuring programmatic advertising remains adaptive, impactful, and aligned with the ever-evolving marketing needs,” Agarwal adds.

AI and machine learning are poised to revolutionize programmatic advertising by 2025, driving significant advancements in campaign planning, execution, and optimization, says Shashidhar Sharma, Head of Programmatic, GroupM Nexus, India.

• Automated Campaign Planning: AI algorithms will analyse vast datasets, including consumer behaviour, media consumption, and campaign performance, to identify the most effective audience segments, media channels, and bidding strategies. This data-driven approach will streamline the planning process and enhance campaign efficiency.
• Real-time optimization: AI/ML tools will continuously monitor campaign performance in real-time, enabling dynamic adjustments to target, bidding, and creative elements. This ensures optimal campaign efficiency and maximizes ROI throughout the campaign lifecycle.
• Focus on strategy and creativity: By automating planning and optimization, AI will free up marketers' time and resources. This allows them to focus on higher-level strategic thinking and develop compelling creative content, leading to more impactful and innovative campaigns.
• Creative optimization: AI technologies like computer vision and generative AI will enable digital marketers to create custom content in real time, matching it to the right audience at the right time. This will make it easier to analyse various ad components and optimize ad creative and placement in near real-time.

Regarding GroupM’s approach, Sharma said that GroupM’s AI Copilot and DSP AI and Custom AI solutions exemplify its commitment to AI-powered innovation in programmatic advertising. These tools leverage human intelligence and AI algorithms to analyse data, predict outcomes, and optimize campaigns for maximum ROI, he adds.

According to Peter Docherty, CTO and Founder, ThinkAnalytics, in 2025, AI will play a pivotal role in generating audience segments for CTV advertising. “It can unlock the value of first-party viewing data, allowing advertisers to accurately reach target audiences and unleashing new revenue opportunities in both contextual and addressable advertising. For example, ThinkAdvertising uses proprietary AI and machine learning algorithms to process billions of viewing behaviours, transforming them into actionable audience segments and affinity categories, alongside household composition data. Both can be used addressably and contextually, and this combination of breadth of data and AI is proven to increase ad engagement and purchases,” says Docherty.

The rise of AI and machine learning is set to redefine programmatic advertising in the coming years, bringing unparalleled precision and scale to campaign management, says Shivangi Singh - Growth Director, Streaming Monetization, Moloco.

“At Moloco, we are already leveraging advanced machine learning algorithms to help advertisers achieve better outcomes by automating complex decision-making processes. In coming years, AI will make campaign planning more predictive and data-driven. Advertisers will be able to analyse audience behaviour in real-time and create dynamic segments that evolve with user interactions. Execution will become more autonomous, with AI systems optimizing creative delivery, ad placement, and bid strategies on the fly, resulting in higher ROI and reduced wastage,” she adds.

“Optimization will also be enhanced by AI’s ability to integrate signals across devices and platforms – something critical for Connected TV (CTV) and mobile convergence, where I’ve seen first-hand how data silos can limit campaign efficacy. Ultimately, AI will empower marketers to focus on strategy and creativity while the technology handles the heavy lifting of execution,” Singh adds.

Right now, when we think of the role of AI in advertising our minds typically go to the way generative AI is used to easily develop creative elements, says Mathieu Roche, CEO and Co-Founder, ID5.

“But generative AI is the visible part of the iceberg in the AI space; the real transformation will come from predictive AI. By harnessing predictive AI the industry will be able to anticipate patterns, improving our ability to identify users with accuracy in the face of signal loss. With fewer signals available, predictive AI and machine learning will become an essential component of ID resolutions,” Roche adds.

Over time, says Gavin Buxton, Managing Director, Asia – Magnite, we’ve seen huge advancements in the way AI and machine learning are being leveraged to improve a wide range of processes across various industries. In programmatic, he adds, machine learning can help make the buying and selling of ads more efficient to drive monetization. It can also significantly reduce the time and resources necessary to process large amounts of data and requests.

“In addition, machine learning can generate recommendations like real-time floor price setting or help personalize ad campaigns. This frees up time and resources for teams to focus on more high-level tasks. In line with this, Magnite recently introduced automated wrapper management within its Demand Manager product to help publishers grow revenue and increase efficiency. Using machine learning, the feature finds the optimal configurations in a publisher’s Prebid wrapper per impression and has the potential to enhance billions of settings to improve performance,” says Gavin Buxton.

Buxton adds that machine learning can also be harnessed to improve inbound and outbound traffic-shaping. With ML applications, publishers can more easily understand buying variations across demand-side platforms to prioritize traffic that optimizes monetization.

In addition, Buxton points out, machine learning tech can be applied to video ad workflows in several ways to improve the streaming ad experience. “Machines are well placed to create the perfect ad break, taking into consideration demand diversity while delivering quality user experiences that yield better results. Automated creative review is yet another use case for AI. Magnite’s SpringServe ad server’s BingeWatcher taps into automation to increase the speed of the creative review process and improve its accuracy, with the added viewer experience benefits of audio normalization, ad de-duplication, and competitive separation,” he adds.

He explains that the rise of AI and machine learning technology has the potential to help the digital advertising industry become more innovative and efficient, while also bringing additional industry-wide benefits, such as enhanced sustainability. “Looking ahead, I expect we’ll continue to find new ways to leverage this technology to further enhance processes.”

(Tomorrow, Part 2 of this feature report will explore how the impending obsolescence of third-party cookies is driving the adoption of privacy-centric targeting and measurement solutions for programmatic advertising in 2025. We'll also examine how advancements in blockchain technology and decentralized platforms are poised to enhance transparency, build trust, and combat fraud within the programmatic ecosystem.)

Also Read: Sanjeev Anand charts out the road ahead for Dentsu Creative PR