by Csongor Fekete | Jun 15, 2025 | AI, Business, Machine Learning
Marketing teams are under-utilizing the full potential of AI, especially in areas that go beyond basic automation, according to a recent article from MarTech. While many teams have adopted AI for content generation and media buying, there are significant gaps in strategic use-cases like customer journey mapping, multichannel personalization, and predictive analytics.
A key learning is that marketing organizations often lack the internal alignment and expertise to implement AI in a holistic way. Most rely on plug-and-play tools that don't cater to their unique data structures or evolving KPIs. This opens space for custom AI models that are purpose-built and designed hand-in-hand with marketing objectives to bring real performance boosts.
One use-case with strong business value is the implementation of a Machine Learning model to predict customer churn by analyzing behavioral and transactional data. Martech leaders can leverage this model to trigger proactive retention campaigns, increasing customer satisfaction and long-term revenue. When paired with precision targeting, such use of AI can reduce acquisition costs and increase ROI — prime goals for any data-driven marketing team.
This highlights the importance of working with an AI agency or AI consultancy equipped to develop context-aware, custom models. Businesses aiming to close the AI utilization gap will benefit from embedding AI experts into their teams and putting data at the center of decision-making.
Read the original article: https://news.google.com/rss/articles/CBMic0FVX3lxTE01R2ZWeHVyTUFpQ0hGb25WU1VlTDJkaVNrbkw4MXpGTHNlaFRtWmVNUXprNW9oS0FXQmFnem03VDZaZmlDYWV1cUd4QnRaSC1yZkJ0c2RzOHhhLVBWc0pXekZWa0p3czJ3NmVQT0ZUX3NGckE?oc=5
by Csongor Fekete | Jun 15, 2025 | AI, Business, Machine Learning
Recent insights from Visual Capitalist’s article “Ranked: The Smartest AI Models, by IQ” highlight the rapid evolution and differentiation of large-scale Machine Learning models—particularly in their general intelligence capabilities. Using standardized IQ testing benchmarks, the article ranks top-performing models like OpenAI’s GPT-4, Anthropic’s Claude 2, and Google DeepMind’s Gemini. The assessment suggests custom-built AI systems are increasingly competitive with or exceeding average human IQ levels.
A key learning here is the diversity in model architecture and deployment strategies. While GPT-4 dominated verbal and reasoning categories, advancements from lesser-known players like Inflection and Alibaba demonstrate niche excellence, indicating that innovation is increasingly democratized. Not all AI models need to be generalist; several excel in domain-specific intelligence. This has critical implications for business adoption.
For marketing and martech sectors, deploying custom AI models tailored to specific verticals—customer segmentation, predictive analytics, campaign personalization—can significantly elevate performance and customer satisfaction. For example, HolistiCrm could apply Machine Learning models calibrated on CRM data to optimize lead scoring or churn prediction. Such precision drives measurable business value: increased conversions, lower acquisition costs, and higher retention.
The rise of IQ benchmarks as a comparative performance metric also underscores the importance of strategic AI consultancy. Businesses must choose or develop models not just for their hype, but for fit, reliability, and mission-critical use cases. Partnering with an AI agency or AI expert can guide enterprises through that complexity to create holistic, high-performing AI solutions.
View original article: https://news.google.com/rss/articles/CBMieEFVX3lxTE5ud3NpdUlrY3RORkxsc29zNW4zbktkdzhNb3A5ZjF6Y2x6SDVpZGcyOUluYTZkbHlzbWlVSWhQN0VVX0hINExPYzJpVDExbDd3ZmVpRmE5eXdiZjkzd1BRYXBLUlY2UkQ1bmw5ZlhvWlVwN19pMXBZRw?oc=5 (original article)
by Csongor Fekete | Jun 14, 2025 | AI, Business, Machine Learning
As artificial intelligence continues to reshape the marketing and advertising landscape, tension is mounting in the creative industries. A recent article by The Guardian explores how agencies and professionals are grappling with automation, fearing a "death of creativity" as generative AI tools grow more capable. While large advertising firms are rapidly adopting AI to generate content and streamline workflows, concerns are rising over job security and the dilution of human creativity.
Key points from the article include:
- Increasing use of AI tools for ad copy, visuals, and strategy is prompting layoffs and restructuring in creative teams.
- Agencies are split: some view AI as an opportunity to enhance performance, others fear it replaces skilled creatives.
- The shift sparks debate on originality and brand identity in algorithm-generated content.
- Advertising insiders emphasize the need for human oversight and ethical boundaries when deploying machine learning models.
For martech-driven businesses and agencies, this raises a crucial use-case opportunity: deploying custom AI models not to replace creativity, but to augment it. A Holistic approach to AI consultancy ensures that Machine Learning models are embedded in a way that supports human talent—optimizing campaign targeting, providing data-driven insights, and reducing rote work, while safeguarding brand tone and strategic vision.
For example, a custom AI model tailored to a retailer’s CRM data can enhance customer segmentation, enabling hyper-personalized marketing that feels genuinely human. This not only boosts performance KPIs but also increases customer satisfaction by delivering content that resonates with individual preferences.
At its core, AI deployment in marketing should not be viewed as a wholesale replacement of creative jobs but as a catalyst for smarter, more efficient brand-building. With guidance from an experienced AI agency, the balance between automation and authentic creativity is not just possible—it’s essential.
Read the original article: The ‘death of creativity’? AI job fears stalk advertising industry – The Guardian
by Csongor Fekete | Jun 14, 2025 | AI, Business, Machine Learning
The recent copyright lawsuit between Getty Images and the London-based AI firm Stability AI is raising critical questions for the AI and martech sectors. At the heart of the case is whether AI companies can legally train Machine Learning models on copyrighted data without explicit permission. Stability AI argues that the legal action, if successful, would not only constrain innovation but also create an “overt threat” to the broader AI industry by limiting access to essential training data.
This legal friction highlights a fundamental challenge facing AI consultancies and AI agencies: how to balance technological advancement with ethical and legal content usage. For companies like HolistiCrm that develop and deploy custom AI models, especially in customer-centric industries such as marketing and customer satisfaction management, this case underlines the necessity of building models using compliant data sources to maintain trust, transparency, and long-term performance.
A practical use-case inspired by this scenario involves HolistiCrm implementing AI-driven marketing personalization engines. By responsibly sourcing data and creating holistic Machine Learning models rooted in transparent data practices, the outcome can be optimized marketing campaigns, improved customer engagement, and enhanced satisfaction—while avoiding legal pitfalls that could erode brand trust.
As enterprises increasingly rely on AI experts to fine-tune Martech tools and decision engines, the importance of model transparency and ethical training material cannot be overstated. This isn't just a legal debate—it's a business continuity issue with real implications for how AI agencies approach model development in 2024 and beyond.
Original article.
by Csongor Fekete | Jun 13, 2025 | AI, Business, Machine Learning
Artificial Intelligence is increasingly central to Europe's technological and economic ambitions, as highlighted during the recent discussions between UK Prime Minister Rishi Sunak and NVIDIA CEO Jensen Huang. In a landmark meeting covered by the NVIDIA Blog, both leaders emphasized the strategic role of AI in driving innovation, enhancing productivity, and shaping future industries across the continent.
The article underscores several key developments:
- The UK is positioning itself as a global AI hub, investing in compute infrastructure and talent.
- NVIDIA’s commitment to Europe includes opening AI research centers and expanding collaborations with universities and industry leaders.
- Ethical AI and safety remain top priorities, with policy deliberations focused on balancing innovation and regulation.
- Custom AI models and next-generation accelerators are seen as vital enablers for sectors such as healthcare, financial services, and climate science.
This sets a compelling use-case for companies in the martech and CRM space. For example, deploying a holistic Machine Learning model trained on customer behavior can significantly boost marketing performance and customer satisfaction. By integrating this intelligence into CRM platforms, such as HolistiCrm, businesses not only optimize campaign targeting but can also anticipate customer needs, personalize messaging, and increase lifetime value.
A custom AI model, supported by an AI consultancy or AI agency, can transform sales pipelines, reduce churn, and enhance decision-making. The strategic vision discussed by leaders like Sunak and Huang signals a strong business case for investing in AI today to stay competitive tomorrow.
Read the original article: https://news.google.com/rss/articles/CBMiX0FVX3lxTE1meW1peVhRaVRKZnNsbDkySDVhX1F6LW5LRlZ6MmlpYkI5RUJDeHdMSjZoNUlhQ0x5MWJLR3gwV0sxNXdBOGZtVWFVNzc1ZllmREE0b18xSGJUNGFoTUM0?oc=5
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