AI vs Traditional: A Definitive Guide for NZ Marketers

New Zealand marketing professionals face a pivotal decision: should they invest in the data-driven precision of AI marketing, or rely on the proven, brand-building power of traditional marketing methods? This isn't just a question of new versus old; it's a strategic choice that will define the future of marketing for New Zealand brands. With 82% of organisations in New Zealand already using artificial intelligence and 93% of them reporting significant efficiency gains, the conversation has moved from if to how AI should be integrated.

This article provides a definitive comparison of AI marketing vs traditional marketing, tailored specifically for the New Zealand market. It moves beyond the hype to deliver a practical, data-supported analysis of each approach's strengths, weaknesses, costs, and returns. The most effective marketing strategies often emerge not from choosing one over the other, but from a thoughtful integration of both, creating a powerful synergy that drives growth and builds lasting brand equity.

Part 1: Defining the Playing Field

To make an informed decision, it is essential to have a clear understanding of what constitutes AI-driven and traditional marketing in today's environment. These definitions establish the foundation for a deeper comparison of their respective strategies and capabilities.

A Look at Today's Data-Driven Strategies

AI marketing is the application of artificial intelligence technologies, machine learning, and advanced data analytics to automate marketing tasks, generate deep customer insights, and deliver hyper-personalised experiences at scale. It represents a fundamental shift from broadcasting messages to engaging in data-informed conversations with individual consumers.

Its core functions include:

Automation: AI systems handle large-scale, repetitive tasks with speed and efficiency. This includes processes like lead scoring, where potential customers are prioritised based on their likelihood to convert, automated email workflows, and real-time bidding for digital ad placements. This frees up human marketers to focus on strategy and creativity.
Personalisation: By analysing vast quantities of customer data—including browsing history, purchase patterns, and real-time behaviour—AI algorithms can deliver individualised product recommendations, tailored content, and relevant offers. This moves beyond basic market segmentation to facilitate true one-to-one communication with customers.
Predictive Analytics: AI marketing tools can forecast future customer behaviour, such as identifying customers at risk of churn or predicting which products will trend next. This allows marketing leaders to develop proactive strategies that anticipate market shifts rather than simply reacting to them.
Content Generation: Generative AI has become a powerful tool for accelerating content creation. It can draft marketing copy, social media posts, email newsletters, and even video scripts. Reports indicate that 43% of marketers currently using AI tools apply them to content creation.

Traditional Marketing: The Enduring Power of Proven Methods

Traditional marketing encompasses any marketing strategy that uses offline media channels to reach an audience. These methods have been the bedrock of brand building for decades and continue to hold relevance in specific contexts.

Key channels and tactics include:

Broadcast Media: Television and radio advertising, which offer broad reach to a mass audience.
Print Media: Advertisements placed in newspapers and magazines, as well as tangible materials like flyers and brochures.
Direct Mail: The delivery of physical marketing materials such as catalogues, postcards, and promotional letters directly to consumers' homes.
Outdoor Advertising: Billboards, transit ads, and other forms of out-of-home (OOH) advertising designed to capture attention in public spaces.
In-Person Events: Direct engagement with customers and prospects through trade shows, conferences, seminars, and sponsored events.

The primary strengths of traditional marketing lie in its ability to build widespread brand awareness, establish credibility through established and trusted media channels, and create tangible, lasting impressions that can lodge a brand in the consumer's memory.

Key Differences: AI-Driven vs Traditional Marketing at a Glance

The fundamental differences between these two approaches are best understood through a direct comparison. The following table provides a scannable overview of their core distinctions across several critical aspects of marketing strategy and execution.

Aspect	AI Marketing	Traditional Marketing
Targeting	Hyper-precise, based on individual behaviour and predictive analytics.	Broad, based on demographics and geography.
Personalisation	Dynamic, one-to-one communication at scale.	Generalised, one-to-many messaging.
Data Analysis	Real-time processing of vast, complex datasets.	Delayed analysis of limited data (e.g., surveys, sales figures).
Measurement & ROI	Direct attribution, clear performance metrics (clicks, conversions).	Difficult attribution, often reliant on correlation.
Scalability	Highly scalable with decreasing marginal costs.	Expensive and resource-intensive to scale.
Speed & Agility	Campaigns can be modified instantly based on performance data.	Campaigns are fixed once launched (e.g., a printed ad).
Cost Structure	Often subscription-based, with scalable investment.	High upfront production and media buying costs.
Human Element	Focus on strategy, creativity, and overseeing AI systems.	Focus on media planning, creative production, and execution.

Part 2: A Head-to-Head Analysis

With the foundational definitions established, a deeper analysis of the specific advantages and disadvantages of each approach is necessary. This examination provides a balanced perspective, incorporating the unique legal and market context relevant to New Zealand marketers.

The Advantages of AI in Marketing: Efficiency, Personalisation, and Predictive Power

The rapid adoption of AI in marketing is driven by clear, measurable benefits that address many of the long-standing challenges in the field.

Improved Efficiency and Productivity

One of the most immediate impacts of AI is its ability to automate repetitive and time-consuming tasks. Research shows that 86% of marketers report AI saves them over an hour each day. By handling tasks like data collection, lead scoring, and basic reporting, AI allows marketing teams to do more with less, shifting their focus from manual execution to high-level strategy, creative development, and complex problem-solving.

Fast and Accurate Data Processing for Deeper Insights

AI algorithms can process and analyse vast customer datasets at a speed and accuracy far beyond human capability. This allows marketers to uncover hidden patterns in purchasing habits, online behaviour, and customer interactions, leading to more effective market segmentation and ad targeting. A significant 64% of marketers use AI specifically to enhance their understanding of customers, which enables them to create marketing materials that align more closely with consumer interests and needs.

Hyper-Personalisation at Scale

AI facilitates a critical shift from broad marketing automation to truly personalised, one-to-one customer experiences. Modern consumers have come to expect this level of individualised attention. AI makes it possible to deliver tailored product recommendations, dynamic website content, and personalised email offers to millions of individuals simultaneously. This leads to higher engagement rates, improved customer retention, and increased conversion probabilities. The success of Spark NZ's personalised campaigns is a powerful local example of this principle in action.

Optimised Campaigns and Enhanced ROI

By analysing campaign performance in real-time, AI systems help marketers optimise their strategies on the fly. Algorithms can automatically adjust ad bids, reallocate budgets to the most effective channels, and test different creative elements to maximise impact. This data-driven optimisation leads to a stronger return on investment. On average, organisations that invest deeply in AI for marketing and sales see their ROI improve by 10–20%.

The Disadvantages and Risks of AI Marketing

While powerful, AI is not without its challenges. For marketers in New Zealand, these risks are not merely technical but also carry significant strategic and legal weight. The country's robust privacy laws present a direct challenge to common AI data practices, making compliance a critical pillar of any AI marketing strategy.

Navigating Data Privacy and the NZ Privacy Act

The effectiveness of AI marketing is built on its ability to process large volumes of data, which inherently raises significant data privacy concerns. In New Zealand, this is governed by the Privacy Act 2020, a piece of legislation that dictates how organisations collect, use, disclose, and store personal information. The Act has extraterritorial scope, meaning it applies to overseas companies doing business in New Zealand, making it relevant for marketers using global AI platforms.

A crucial development for marketers is the Privacy Amendment Bill, which introduces a new Information Privacy Principle (IPP 3A). This principle, set to take effect in 2026, will require organisations to take reasonable steps to notify individuals when their personal information is collected indirectly—that is, from a third-party source rather than directly from the individual concerned. This creates a direct conflict with AI models that rely on aggregating third-party data to enrich customer profiles for lead scoring or personalisation.

For NZ marketers, this transforms data privacy from a generic concern into a specific and urgent compliance hurdle. It necessitates a strategic shift towards prioritising first-party data (information given directly by the customer with consent) and transparent data collection practices. An "ethical AI" approach, built on a foundation of clear consent, is no longer just a buzzword but a legal necessity and a potential competitive differentiator.

The Challenge of AI Bias and Inaccuracy

An AI system's output is a direct reflection of the data it was trained on. If that data is incomplete, outdated, or contains historical biases, the AI's predictions and generated content will be biased or inaccurate. This can lead to unfairly targeted advertising, discriminatory outcomes, or brand damage. Furthermore, generative AI tools can sometimes produce "AI hallucinations"—outputs that are factually incorrect or nonsensical. This risk underscores the non-negotiable need for human oversight. Even with advanced AI, 86% of marketers who use AI-generated content still spend time editing and verifying it to ensure quality and accuracy.

The Lack of Human Creativity and Emotional Nuance

While AI can generate text, images, and videos based on existing patterns, it cannot replicate genuine human creativity, empathy, or emotional intelligence. AI operates without consciousness or feeling; it cannot understand the subtle cultural nuances and emotional triggers that build deep, lasting connections between a brand and its audience. This fundamental limitation highlights why AI should be viewed as a tool to assist the human marketer, not replace them. The roles that require strategic storytelling, brand guardianship, and creative vision remain firmly in the human domain.

Is Traditional Marketing Still Effective in New Zealand?

In an era dominated by digital metrics, it is easy to dismiss traditional marketing. However, its value in New Zealand is amplified by the country's unique market characteristics. The "wide net" approach, often seen as a weakness in larger markets, can be a distinct strength in a smaller, less fragmented media landscape. Similarly, its tangibility and association with trusted local media can resonate deeply in a high-trust, community-oriented culture.

Where Traditional Marketing Strategies Still Win Hearts and Minds

Building Trust and Credibility: Traditional media channels like established newspapers, national television, and local radio are often perceived by consumers as more credible and professional than online ads, helping to build foundational brand trust.
Wide Reach and Brand Awareness: For establishing top-of-mind awareness across a broad demographic, traditional channels remain exceptionally powerful. Television advertising, for instance, still reaches the vast majority of households, and global spending on traditional advertising is projected to rebound to $1.75 trillion in 2024, signalling its continued relevance.
Tangibility and Permanence: A physical advertisement, such as a direct mail piece or a well-placed magazine ad, creates a lasting, tangible impression that a fleeting digital ad cannot replicate. This physical presence can keep a brand in a consumer's home or office for days or weeks.
Reaching Specific Demographics: A significant portion of the population, particularly within older demographics, continues to value and actively consume traditional forms of media, making these channels essential for reaching them effectively.

The Main Challenges: Measurement, Cost, and Targeting

Despite its strengths, traditional marketing faces significant and well-documented challenges in the modern era.

Difficult Attribution and Measurement: The primary drawback is the inability to accurately measure return on investment. It is nearly impossible to determine precisely which billboard, radio spot, or newspaper ad led directly to a sale. This lack of direct attribution makes it incredibly difficult to optimise campaigns based on performance data.
High Upfront Costs: Traditional marketing typically requires a substantial initial investment in creative production and media buying. This makes it a high-risk proposition, particularly for small and medium-sized businesses with limited budgets.
Limited Targeting Capabilities: The broad, "wide net" approach inevitably leads to wasted ad spend, as messages are delivered to large audiences who are not potential customers. This lack of precision is a stark contrast to the hyper-targeting capabilities of digital and AI-driven methods.
Lack of Flexibility: Once a traditional campaign is launched, it is largely set in stone. A mistake in a print run or a poorly received television ad cannot be easily corrected, making costly errors irreversible.

Part 3: The Financial Realities

Understanding the financial implications of each approach is crucial for marketing leaders tasked with allocating budgets and justifying expenditure. This section provides a practical, numbers-driven comparison of the costs and potential returns associated with both AI-driven and traditional marketing.

Cost vs. ROI: A Financial Breakdown for NZ Marketers

The cost structures for AI and traditional marketing are fundamentally different. Traditional marketing is characterised by high upfront costs for production and media placement, while AI marketing often involves more predictable, subscription-based models and implementation fees. The following table provides a comparative financial breakdown to help guide budget decisions.

Channel/Tool	Typical Upfront Cost	Typical Ongoing Cost (Monthly)	Typical ROI Potential
Traditional Marketing
TV Commercial	High ($50k - $500k+ production)	Very High (media slots can be $100k+)	71% average for established brands
Full-Page Magazine Ad	High ($20k - $300k)	N/A	80% for local businesses
Direct Mail Campaign	Moderate (design/print)	Moderate-High ($8k - $12k for 20k pieces)	29% median ROI
Billboard Rental	Low-Moderate	Moderate ($1.5k - $15k)	Varies, harder to track
AI Marketing
AI Tools Subscription	Low-Moderate ($100 - $5k)	Low-Moderate ($100 - $5k)	Varies by channel
Implementation & Training	Moderate-High ($10k - $50k one-off)	N/A	Foundational for all other ROI
Data Infrastructure	Moderate-High ($5k - $50k setup)	Low (maintenance)	Foundational for all other ROI
AI-Optimised Email	Low	Low	Up to 42:1 (4,200%)
AI-Optimised SEO	Low	Low-Moderate	22:1 average

Measuring the True Return on Investment for Both Approaches

While the table provides benchmarks, understanding the nuances behind these ROI figures is critical.

The path to achieving a positive return from AI marketing is not always straightforward. A striking 74% of enterprises report that they fail to capture sufficient value from their AI initiatives. This "AI value struggle" is rarely due to failures in the technology itself. Instead, it stems from more fundamental issues: inadequate or poor-quality data, a lack of skilled talent to manage the systems, and the absence of a clear, strategic vision for how AI will be used.

Successful organisations understand that AI implementation is not just a technology project but a business transformation. Analysis shows that leading companies allocate their resources according to a 70/20/10 rule: 70% is invested in people and processes (training, workflow redesign), 20% in technology and data infrastructure, and only 10% in the algorithms themselves. This demonstrates that ROI is unlocked through a holistic, strategic implementation that prioritises human capital and operational readiness.

Conversely, the ROI of traditional marketing includes intangible, long-term brand value that is difficult to quantify but compounds over years. The trust, credibility, and top-of-mind awareness built by a consistent presence in traditional media may not show up in last-click attribution models but are invaluable assets for long-term growth.

In summary, AI marketing offers the potential for a higher, more measurable, and direct-response ROI, but only when implemented correctly with a strong focus on data, people, and strategy. Traditional marketing provides a less quantifiable but powerful long-term brand-building ROI that remains a vital component of a balanced marketing mix.

Part 4: The New Zealand Perspective

To be truly useful, any comparison of marketing strategies must be grounded in the local context. This section examines AI adoption rates, successful case studies, and the unique market challenges specific to New Zealand, providing a tailored perspective for marketers in Aotearoa.

AI in Action: How New Zealand Businesses are Gaining an Edge

Artificial intelligence is not a theoretical concept in New Zealand; it is a practical tool delivering tangible results. An impressive 82% of NZ organisations have adopted AI, with the majority (72%) opting for accessible, off-the-shelf solutions rather than custom builds. The impact is clear: 93% of these businesses report gains in worker efficiency, and 56% have seen a positive financial impact. Notably, marketing is ranked among the top five business functions where AI is being applied, demonstrating its central role in driving growth for Kiwi companies.

NZ Example: Spark NZ's Hyper-Personalisation Journey

Spark NZ provides a world-class example of AI-driven marketing success. Facing the challenge of moving beyond generic customer communication, Spark sought to build deeper relationships and drive cross-selling opportunities. By combining its in-house AI and machine learning capabilities with the Adobe Experience Cloud platform, Spark began delivering proactive, highly personalised mobile and broadband plan recommendations based on individual customer usage data.

NZ Example: Auckland Airport's AI-Enhanced Customer Experience

Auckland Airport aimed to improve communication and create a seamless, helpful experience for the millions of travellers passing through its terminals. Using Adobe's Journey Optimizer platform, the marketing team orchestrated timely and relevant automated messages tailored to each traveller's specific journey. For example, a passenger might receive a reminder about their parking booking upon arrival, followed by a personalised retail offer based on their preferences.

Insights from Foodstuffs, Stuff Group, and other Kiwi Innovators

The application of AI in New Zealand extends across various industries:

Foodstuffs NZ: During the COVID-19 pandemic, the supermarket giant used the AI platform Yabble to instantly analyse vast amounts of unstructured consumer feedback. This allowed them to detect early signals of panic-buying behaviour and adjust their supply chain and operational plans accordingly, demonstrating AI's power in real-time market analysis.
Stuff Group: New Zealand's largest media company is piloting an AI program to translate news articles into te reo Māori at scale. This initiative shows how AI can be used not only for commercial goals but also to support important cultural and corporate objectives.
Other Innovators: Companies like ASB Bank (AI-powered customer service chatbot), Toyota Finance NZ (robotic process automation for loan approvals), and Aider (AI-driven analytics for small businesses) further illustrate the breadth of AI adoption and its impact on productivity across the New Zealand economy.

Navigating the Unique Challenges of the NZ Marketing Landscape

The primary challenges faced by New Zealand marketers—including geographic isolation, a small market scale, and a persistent digital divide—also serve as powerful catalysts for AI adoption. Artificial intelligence directly addresses these pain points by offering global reach, operational efficiency, and access to data-driven strategies that enable smaller teams to compete effectively with larger, international players.

Geographic Isolation and Local Intent: New Zealand's location means that a high percentage of online search queries have a strong local intent. This makes Local SEO and a well-optimised Google Business Profile critical for visibility. It is an area where traditional marketing (a physical local presence) and digital marketing must be closely aligned to succeed.
Small Market Size and Competition: The relatively small domestic market has historically meant less intense competition, which can lead to slower rates of innovation. However, the rise of global eCommerce is bringing international competitors directly to the doorsteps of Kiwi consumers. AI allows smaller New Zealand brands to counter this by being more agile, targeted, and efficient. They can use data-driven strategies to outmanoeuvre larger, slower-moving global companies that may lack nuanced local insights.
Economic Pressures and Cautious Consumers: With New Zealand facing recessionary pressures and consumers remaining more cautious with their spending, marketers are under increased pressure to demonstrate a clear return on investment. AI analytics are invaluable for optimising marketing spend and eliminating waste. At the same time, AI-powered personalisation helps brands create value-driven offers and communications that resonate with budget-conscious consumers, making them feel understood and valued.
The Digital Divide: Many New Zealand businesses, particularly SMEs, report lacking the time, knowledge, and resources to make the right digital choices. Cybersecurity is also cited as a major barrier to digital adoption. This highlights a critical need for accessible, user-friendly AI tools and widespread education on best practices to ensure all businesses can benefit from this technological shift.

Part 5: The Future-Ready Marketer

The final piece of the puzzle is to translate this analysis into actionable advice. This section focuses on the strategic integration of AI and traditional marketing, the evolving skills required for success, and a practical guide for getting started.

The Future of Marketing: Why a Hybrid Strategy is Your Best Bet

The debate should not be framed as "AI versus traditional marketing." The most sophisticated and successful marketing leaders understand that the winning move is to not treat these approaches as rivals but instead blend their respective strengths into a cohesive, integrated strategy.

This hybrid model leverages each approach for what it does best. AI is used for data analysis, automation, and delivering personalisation at a scale that would be impossible for humans to manage. At the same time, traditional marketing is deployed to build broad brand awareness, establish foundational trust through credible media channels, and create the tangible, emotional connections that forge lasting brand loyalty.

An example of an integrated campaign could look like this: A Kiwi brand uses AI-driven analytics to identify a high-value niche audience segment. It then targets this segment with a hyper-personalised digital advertising and email campaign (AI's strength). Simultaneously, it runs a broader brand-building campaign on a popular local radio station or in a targeted industry magazine (traditional's strength). This surrounds the target customer with a consistent message across multiple touchpoints, combining the precision of digital with the credibility of traditional media.

How AI is Changing Marketing Jobs and the Skills You'll Need

Artificial intelligence is not eliminating marketing jobs; it is reframing them. By automating routine and repetitive tasks, AI is elevating the role of the marketer, allowing professionals to focus on higher-level functions like strategy, creativity, data interpretation, and customer experience design.

While this shift creates immense opportunity, it also brings anxiety. Nearly 60% of marketers express concern that AI may one day replace their roles. However, the same analysis predicts that while some tasks will be automated, AI will also help create 97 million new roles globally by 2030. The key to thriving in this new environment is adaptation and upskilling.

The essential skills for the future-ready NZ marketer include:

Data Literacy: The ability to not only understand the data and insights provided by AI systems but also to critically interpret and question them.
Strategic Thinking: The capacity to use AI-generated insights as a foundation for formulating and refining overarching marketing strategies that align with business goals.
Prompt Engineering: The emerging skill of crafting clear, specific, and effective prompts to elicit the best possible output from generative AI tools for content creation and analysis.
Creativity & Storytelling: The uniquely human ability to weave data points and product features into a compelling brand narrative that resonates emotionally with an audience—something AI cannot replicate.
Ethical Governance: A deep understanding of the ethical implications of AI, particularly concerning data privacy, algorithmic bias, and transparency, and the ability to implement and oversee responsible AI practices.

Getting Started: A Practical Guide for Integrating AI into Your Strategy

For small and medium-sized businesses in New Zealand, adopting AI can seem daunting. A practical, step-by-step approach can demystify the process.

Identify Your Goals and Pain Points: Do not adopt AI for its own sake. Start by identifying specific, measurable business problems that need solving. Are your lead response times too slow? Is your customer segmentation ineffective? Are you spending too much time on manual content creation? A clear problem statement will guide your AI selection process.
Start Small and Leverage Existing Tools: Many of the software platforms your business already uses—such as Google Workspace, Shopify, or HubSpot—have powerful AI features built-in. Experiment with these low-cost, low-risk options first to understand their capabilities and build your team's confidence.
Prioritise Your Data: Before you invest in advanced AI systems, you must get your data in order. Ensure your customer data is clean, organised, accessible, and compliant with privacy regulations. Data quality is the single most important factor determining the success or failure of any AI initiative.
Explore Key AI Tool Categories: Once you have a clear goal, explore tools designed for that purpose. Key categories for marketers include:
- Content Creation & SEO: Tools like Jasper, ChatGPT, and Keyword Insights can assist with brainstorming, drafting copy, and optimising for search.
- Social Media Management: Platforms like Sprout Social and Ocoya use AI to schedule posts, analyse sentiment, and identify trends.
- Advertising: Tools like Adcreative.ai can generate and test ad variations at scale.
- Customer Service & Chatbots: Solutions like Tidio and Drift can automate responses to common customer queries on your website.
Evaluate Risks and Plan for Oversight: Before deploying any AI tool, consider the risks. Evaluate its data security protocols, be aware of the potential for inaccurate outputs, and ensure it can be used in compliance with the NZ Privacy Act. Critically, always maintain a "human in the loop" to review, edit, and approve AI-generated work before it goes public.

Final Thoughts: Making the Right Choice for Your Brand

The evidence is clear: the most powerful marketing approach for New Zealand businesses in 2025 and beyond is not a binary choice between artificial intelligence and traditional methods. It is a strategic and seamless integration of both. AI provides the data-driven efficiency and hyper-personalised precision necessary to compete in a globalised digital marketplace. At the same time, traditional marketing continues to offer unparalleled strengths in building the broad brand awareness, trust, and emotional resonance that are essential in the unique New Zealand market. The future-ready marketer is not a technologist or a traditionalist, but a skilled orchestrator who can harness the best of both worlds to drive sustainable growth.

Frequently Asked Questions (FAQ)

Q: Can AI completely replace traditional marketing?

A: No. While AI excels at data-driven tasks like automation, analysis, and personalisation, traditional marketing remains superior for building broad brand awareness, establishing credibility, and forging deep emotional connections with an audience. The most effective strategies do not replace one with the other but combine the strengths of both for a holistic approach.

Q: What are the best AI marketing tools for a small NZ business?

A: The best starting point is to explore the AI features already built into the platforms you use daily, such as Google Workspace, HubSpot, or Shopify. For specific needs, consider user-friendly tools like Jasper for content creation, Tidio for website chatbots, or Adcreative.ai for social media ads. The key is to choose a tool that solves a specific business problem rather than adopting technology for its own sake.

Q: How does AI marketing handle data privacy in New Zealand?

A: This is a critical consideration for all marketers. Any AI system used in New Zealand must comply with the Privacy Act 2020. This means being transparent about how customer data is collected and used. Marketers must also prepare for upcoming changes like IPP 3A, which will require notification when personal data is collected from third-party sources. Prioritising first-party data collection (with clear consent) and selecting AI tools with robust privacy and security features is essential for compliance.

Q: What's the biggest mistake marketers make when implementing AI?

A: The most common mistake is focusing solely on the technology while neglecting the foundational elements. Many AI projects fail not because the algorithm is flawed, but because of poor data quality, the absence of a clear strategy, and inadequate team training and upskilling. Successful AI implementation requires a significant investment in people and processes, not just in software.

Q: How can I measure the ROI of my AI-driven marketing efforts?

A: Measure the impact of AI against specific, goal-oriented metrics. For instance, if you use AI for email personalisation, track the uplift in open rates, click-through rates, and conversions compared to your previous baseline. If you implement an AI-powered lead scoring system, measure the increase in sales-qualified leads and the reduction in your cost per acquisition. Tying AI usage to clear business outcomes is the key to demonstrating its ROI.

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