AI Digital Debuts AI Digital Labs to Power Client Transformation, with a growth-focused AI leader at the helm
Tatev Malkhasyan
May 21, 2025
3
minutes read
With its strategic hire and innovation hub investment, AI Digital doubles down on its commitment to turning AI from buzzword to business-critical value for brands and agencies navigating the evolving media landscape.
NEW YORK, May 21, 2025—AI Digital, the leading end-to-end programmatic consultancy, today unveiled AI Digital Labs, a hands-on transformation practice helping clients turn AI ambition into action. To lead this effort, AI Digital has named David Mainiero its first Chief AI Officer.
As AI adoption accelerates across advertising, marketers face mounting pressure to deliver clear, measurable outcomes. AI Digital has long helped clients meet that challenge through holistic, platform-agnostic solutions and its “Open Garden” framework. The rollout of AI Digital Labs builds on the momentum of Elevate, its flagship AI-powered marketing intelligence platform, and marks a deeper investment in practical, end-to-end enablement. More than just access to tools, AI Digital Labs delivers workflow-ready AI to help advertisers outpace disruption and execute with urgency.
“The industry doesn’t need another slide-deck on AI–it needs partners who can build, ship, and scale real solutions now,” said Stephen Magli, CEO at AI Digital. “With AI Digital Labs, we’re reinforcing our promise to drive business-critical results for our clients. David’s leadership and vision make that promise even stronger.”
David Mainiero brings a rare blend of enterprise-scale AI transformation and hands-on growth-stage leadership. He led AI enablement at Factor, building AI-powered service lines from the ground up and helping Fortune 100 clients operationalize AI at scale. He also co-founded InGenius Prep, a global education consultancy scaled from startup to category leader. With deepexperience in high-growth sectors requiring nuanced domain expertise, David has consistently operated at the intersection of strategy, technology, and execution. At AI Digital, David will serve as both external evangelist and internal strategist, advancing AI Digital’s capabilities across three key fronts:
Client enablement: Through AI Digital Labs, Mainiero will embed AI directly into client operating models by deploying bespoke agents and tooling and offer comprehensive transformation support through executive workshops and targeted upskilling and training programs.
Thought leadership & innovation hub: David will champion industry education and thought leadership, launching an AI content series, executive workshops, and strategic partnerships that drive AI fluency across the ecosystem. A key initiative will be formally certifying teams in the practical application of the company’s "Elevated Intelligence" methodology, tailored to real-world workflows and challenges.
Product innovation: He will co-lead the development of Elevate, AI Digital's proprietary intelligence platform, expanding it from optimizer to strategic engine with real-time insights, predictive planning, and transparent AI recommendations.
“What drew me to AI Digital is the rare opportunity to build the future of media with a team that moves fast, thinks boldly, and delivers real impact,” said David Mainiero, Chief AI Officer at AI Digital. “AI is a new way of working, thinking, and creating. Our job is to embed that mindset across everything we do, from how we plan campaigns to how we design tools like Elevate, our AI-powered marketing intelligence engine. AI Digital is already at the forefront; now, we’re here to define what comes next.”
With the debut of AI Digital Labs and the appointment of Mainiero, AI Digital reinforces its position as a true AI-first, end-to-end programmatic consultancy, calibrating the right blend of cutting-edge technology, niche expertise, and practical outcome-orientation needed to make AI truly work for its clients. As agencies and advertisers demand more than experimentation, AI Digital Labs embodies the company’s vision for AI-powered, human-driven advertising, providing the guidance, tools, and executional confidence to turn AI into a lasting business advantage.
David Mainiero, Chief AI Officer
About AI Digital
Founded in 2018, AI Digital is a leading end-to-end programmatic consultancy with over 300 strategists working globally. The company partners with all major advertising platforms across 15+ DSPs, including Amazon, Google, and The Trade Desk. AI Digital's technology-agnostic approach provides clients access to inventory across all media channels while analyzing consumer data for precision targeting. The proprietary Elevate platform connects data, platforms, and inventory for transparent, measurable advertising solutions. By combining strategy, technology, and insights, AI Digital drives measurable business outcomes for mid-size agencies and brands. For more information, visit www.aidigital.com or contact pr@aidigital.com.
For more information, contact: Tatev Malkhasyan
Marketing Director
pr@aidigital.com
Blind spot
Key issues
Business impact
AI Digital solution
Lack of transparency in AI models
• Platforms own AI models and train on proprietary data • Brands have little visibility into decision-making • "Walled gardens" restrict data access
• Inefficient ad spend • Limited strategic control • Eroded consumer trust • Potential budget mismanagement
Open Garden framework providing: • Complete transparency • DSP-agnostic execution • Cross-platform data & insights
Optimizing ads vs. optimizing impact
• AI excels at short-term metrics but may struggle with brand building • Consumers can detect AI-generated content • Efficiency might come at cost of authenticity
• Short-term gains at expense of brand health • Potential loss of authentic connection • Reduced effectiveness in storytelling
Smart Supply offering: • Human oversight of AI recommendations • Custom KPI alignment beyond clicks • Brand-safe inventory verification
The illusion of personalization
• Segment optimization rebranded as personalization • First-party data infrastructure challenges • Personalization vs. surveillance concerns
• Potential mismatch between promise and reality • Privacy concerns affecting consumer trust • Cost barriers for smaller businesses
Elevate platform features: • Real-time AI + human intelligence • First-party data activation • Ethical personalization strategies
AI-Driven efficiency vs. decision-making
• AI shifting from tool to decision-maker • Black box optimization like Google Performance Max • Human oversight limitations
• Strategic control loss • Difficulty questioning AI outputs • Inability to measure granular impact • Potential brand damage from mistakes
Managed Service with: • Human strategists overseeing AI • Custom KPI optimization • Complete campaign transparency
Fig. 1. Summary of AI blind spots in advertising
Dimension
Walled garden advantage
Walled garden limitation
Strategic impact
Audience access
Massive, engaged user bases
Limited visibility beyond platform
Reach without understanding
Data control
Sophisticated targeting tools
Data remains siloed within platform
Fragmented customer view
Measurement
Detailed in-platform metrics
Inconsistent cross-platform standards
Difficult performance comparison
Intelligence
Platform-specific insights
Limited data portability
Restricted strategic learning
Optimization
Powerful automated tools
Black-box algorithms
Reduced marketer control
Fig. 2. Strategic trade-offs in walled garden advertising.
Core issue
Platform priority
Walled garden limitation
Real-world example
Attribution opacity
Claiming maximum credit for conversions
Limited visibility into true conversion paths
Meta and TikTok's conflicting attribution models after iOS privacy updates
Data restrictions
Maintaining proprietary data control
Inability to combine platform data with other sources
Amazon DSP's limitations on detailed performance data exports
Cross-channel blindspots
Keeping advertisers within ecosystem
Fragmented view of customer journey
YouTube/DV360 campaigns lacking integration with non-Google platforms
Black box algorithms
Optimizing for platform revenue
Reduced control over campaign execution
Self-serve platforms using opaque ML models with little advertiser input
Performance reporting
Presenting platform in best light
Discrepancies between platform-reported and independently measured results
Consistently higher performance metrics in platform reports vs. third-party measurement
Fig. 1. The Walled garden misalignment: Platform interests vs. advertiser needs.
Key dimension
Challenge
Strategic imperative
ROAS volatility
Softer returns across digital channels
Shift from soft KPIs to measurable revenue impact
Media planning
Static plans no longer effective
Develop agile, modular approaches adaptable to changing conditions
Brand/performance
Traditional division dissolving
Create full-funnel strategies balancing long-term equity with short-term conversion
Capability
Key features
Benefits
Performance data
Elevate forecasting tool
• Vertical-specific insights • Historical data from past economic turbulence • "Cascade planning" functionality • Real-time adaptation
• Provides agility to adjust campaign strategy based on performance • Shows which media channels work best to drive efficient and effective performance • Confident budget reallocation • Reduces reaction time to market shifts
• Dataset from 10,000+ campaigns • Cuts response time from weeks to minutes
• Reaches people most likely to buy • Avoids wasted impressions and budgets on poor-performing placements • Context-aligned messaging
• 25+ billion bid requests analyzed daily • 18% improvement in working media efficiency • 26% increase in engagement during recessions
Full-funnel accountability
• Links awareness campaigns to lower funnel outcomes • Tests if ads actually drive new business • Measures brand perception changes • "Ask Elevate" AI Chat Assistant
• Upper-funnel to outcome connection • Sentiment shift tracking • Personalized messaging • Helps balance immediate sales vs. long-term brand building
• Natural language data queries • True business impact measurement
Open Garden approach
• Cross-platform and channel planning • Not locked into specific platforms • Unified cross-platform reach • Shows exactly where money is spent
• Reduces complexity across channels • Performance-based ad placement • Rapid budget reallocation • Eliminates platform-specific commitments and provides platform-based optimization and agility
• Coverage across all inventory sources • Provides full visibility into spending • Avoids the inability to pivot across platform as you’re not in a singular platform
Fig. 1. How AI Digital helps during economic uncertainty.
Trend
What it means for marketers
Supply & demand lines are blurring
Platforms from Google (P-Max) to Microsoft are merging optimization and inventory in one opaque box. Expect more bundled “best available” media where the algorithm, not the trader, decides channel and publisher mix.
Walled gardens get taller
Microsoft’s O&O set now spans Bing, Xbox, Outlook, Edge and LinkedIn, which just launched revenue-sharing video programs to lure creators and ad dollars. (Business Insider)
Retail & commerce media shape strategy
Microsoft’s Curate lets retailers and data owners package first-party segments, an echo of Amazon’s and Walmart’s approaches. Agencies must master seller-defined audiences as well as buyer-side tactics.
AI oversight becomes critical
Closed AI bidding means fewer levers for traders. Independent verification, incrementality testing and commercial guardrails rise in importance.
Fig. 1. Platform trends and their implications.
Metric
Connected TV (CTV)
Linear TV
Video Completion Rate
94.5%
70%
Purchase Rate After Ad
23%
12%
Ad Attention Rate
57% (prefer CTV ads)
54.5%
Viewer Reach (U.S.)
85% of households
228 million viewers
Retail Media Trends 2025
Access Complete consumer behaviour analyses and competitor benchmarks.
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Michaels Stores: Implemented a genAI platform that increased email personalization from 20% to 95%, leading to a 41% boost in SMS click through rates and a 25% increase in engagement.
Estée Lauder: Partnered with Google Cloud to leverage genAI technologies for real-time consumer feedback monitoring and analyzing consumer sentiment across various channels.
High
Medium
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Showmax: Partnered with AI firms toautomate ad creation and testing, reducing production time by 70% while streamlining their quality assurance process.
Headway: Employed AI tools for ad creation and optimization, boosting performance by 40% and reaching 3.3 billion impressions while incorporating AI-generated content in 20% of their paid campaigns.
High
High
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
L’Oréal: Analyzed millions of online comments, images, and videos to identify potential product innovation opportunities, effectively tracking brand sentiment and consumer trends.
Kellogg Company: Used AI to scan trending recipes featuring cereal, leveraging this data to launch targeted social campaigns that capitalize on positive brand sentiment and culinary trends.
High
Low
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
DoorDash: Leveraged Google’s AI-powered Demand Gen tool, which boosted its conversion rate by 15 times and improved cost per action efficiency by 50% compared with previous campaigns.
Kitsch: Employed Meta’s Advantage+ shopping campaigns with AI-powered tools to optimize campaigns, identifying and delivering top-performing ads to high-value consumers.
High
High
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
JPMorgan Chase: Collaborated with Persado to develop LLMs for marketing copy, achieving up to 450% higher clickthrough rates compared with human-written ads in pilot tests.
Hotel Chocolat: Employed genAI for concept development and production of its Velvetiser TV ad, which earned the highest-ever System1 score for adomestic appliance commercial.
High
High
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
Stitch Fix: Uses genAI to help stylists interpret customer feedback and provide product recommendations, effectively personalizing shopping experiences.
Instacart: Uses genAI to offer customers personalized recipes, mealplanning ideas, and shopping lists based on individual preferences and habits.
Medium
Medium
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