thomas.wieberneit@aheadcrm.co.nz
The Great GenAI Divide: Debunking the Myth of 95% Failure

The Great GenAI Divide: Debunking the Myth of 95% Failure

These days, we are drowning in conflicting information about the value of generative and/or agentic AI. I, myself am researching for good studies that dive into the ROI that is generated by this technology, with limited success. Most information is anecdotal, or comes from success stories, which cannot get used too literally. Two major 2025 reports from MIT and Wharton, respectively, paint starkly different pictures of AI adoption and adoption success. While the meanwhile often quoted MIT NANDA “report” on the state of AI in business often gets quoted with 95 percent of all businesses not getting any ROI from their gen AI initiatives, a recent study by the Wharton Business School shows a very different result with 74 per cent of enterprises showing a positive ROI. Why is one so pessimistic and the other so optimistic? As I have written before, a closer look at the data reveals the 95% “failure” narrative is a myth, or even a scare, and the real story is probably a different and far more differentiated one, which Wharton names Accountable Acceleration. Is GenAI really a 1-in-20 lottery ticket or is it rather a core business function? So, let’s have a look. Methodology matters – debunking the 95% failure rate In contrast to the NANDA “report” that relies on a fairly small sample of about 150 survey responses and 52 structured interviews, the. Wharton report bases on a large-scale, quantitative and longitudinal study. It surveyed around 800 senior decision-makers at businesses of different sizes and is tracking trends for the third consecutive year. Therefore, its data is built for statistically valid conclusions. In...
Zoho goes all in with AI – bold or inevitable?

Zoho goes all in with AI – bold or inevitable?

The news On July 17, 2025 Zoho launched Zia LLM and deepened its AI portfolio with agents, an agent builder, MCP support and an agent marketplace. Key announcements from the press release include: In-House LLM: Zoho has developed its own large language model, Zia LLM, which comes in three sizes (1.3B, 2.6B, and 7B parameters) to optimize for different business use cases. This allows customers to leverage AI while keeping their data within Zoho’s ecosystem, ensuring privacy. The three models allow Zoho to always optimize the right model for the right user context, striking the proper balance between power and resource management. This focus on right-sizing the model is an ongoing development strategy for Zoho. Speech-to-Text Models: The company also unveiled two proprietary Automatic Speech Recognition (ASR) models for English and Hindi, with plans to support more languages in the future. Prebuilt AI Agents: To facilitate immediate adoption, Zoho has introduced a range of AI agents that are integrated directly into its products. These agents are designed to automate tasks for various business roles such as sales development, customer support, and account management. Global and Private Cloud Deployment: The new Zia LLM will be deployed across Zoho’s data centers in the US, India, and Europe. Continued Support for Other Models: While promoting its own AI, Zoho will continue to support integrations with other popular large language models like ChatGPT, Llama, and DeepSeek. Zoho will continue to scale Zia LLM’s mode sizes. A2A capabilities are on the roadmap. The bigger picture Enterprise software has been a platform game for a long time. AI, in particular generative and agentic AI, have...
Creatio goes agentic but adds an interesting twist

Creatio goes agentic but adds an interesting twist

The news On June 25, Creatio announced the launch of version 8.3 of its platform, dubbed as the “Twin release”. The release features new prebuilt role-based AI agents, a unified conversational interface, and AI-powered no-code development tools. These new capabilities are natively embedded into the core of the platform. According to Creatio, the “Twin” release reflects the company’s vision of AI as a collaborative force within the enterprise. Katherine Kostereva, CEO at Creatio, stated, “Our approach is human-centric. With this release, we continue to expand our AI-native platform, placing unified, actionable, and composable AI automation at the very core of Creatio. The 8.3 release takes our AI automation to a new level, empowering organizations to transform processes and deliver results like never before.” Key innovations in this release include Natively Embedded AI and a Unified Conversational Interface: The 8.3 “Twin” Release advances Creatio’s AI-native strategy by embedding Creatio’s AI deeper into and across every layer of the platform. Creatio.ai is designed to power real-time automation, provide grounded recommendations, and offer a seamless natural language experience. Users can now interact with Creatio using natural language as the default mode through a refreshed, AI-optimized interface. The assistant utilizes retrieval-augmented generation (RAG) to provide responses based on company-specific context. These conversational capabilities are natively available across Creatio’s web and mobile applications, as well as within productivity tools such as MS Outlook and MS Teams. Prebuilt, Role-Based AI Agents: The release introduces new prebuilt, role-based AI agents that cover sales, service, marketing and development. These agents are designed to help employees and customers achieve business results faster. AI-Powered No-Code Development: Creatio 8.3 enhances...
Agentforce 3 – finally ready for the enterprise?

Agentforce 3 – finally ready for the enterprise?

The news On June 23, 2025, Salesforce announced Agentforce 3, the third iteration of its Agentforce platform. Agentforce 3 is a major upgrade to Salesforce’s digital labor platform. It gives customers the visibility and control that is needed to scale AI agents that already have proven useful at many companies. The release covers several additional capabilities. Salesforce has introduced the Agentforce Command Center, an observability console designed for managing AI agents. This tool allows businesses to track and scale AI agent activities. It is built into Agentforce Studio and includes features for monitoring performance metrics such as latency and error rates through live analytics. The update also brings native support for the Model Context Protocol (MCP), which enables Agentforce to connect with any MCP-compliant server without requiring custom coding. The platform’s Atlas architecture has been enhanced to improve latency, accuracy, and resiliency. Support for additional Large Language Models has been added, including Anthropic’s Claude Sonnet via Amazon Bedrock, with future support planned for Google Gemini. Agentforce 3 includes over 200 pre-built industry actions, with half of these being new additions. The agents are now capable of performing web searches and providing citations for the information they retrieve. The platform’s availability has been expanded to Canada, the U.K., India, Japan, and Brazil, adding support for six new languages. More than 30 new partners have been added to the AgentExchange marketplace. These include companies such as AWS, Box, Cisco, Google Cloud, IBM, PayPal, and Stripe. Salesforce has also introduced new pricing options, including per-user plans for its Sales, Service, and Industry Clouds that provide unlimited usage of actions for employee-facing agents....
The CDP is dead – long live the CDP!

The CDP is dead – long live the CDP!

In the past few years, I have written about CDPs, what they are and what their value is – or rather can be. My definition of a CDP that I laid out in one of my column articles on CustomerThink is: A Customer Data Platform is a software that creates persistent, unified customer records that enable business processesthat have the customers’ interests and objectives in mind. It is a good thing that CDPs evolved from its origins of being a packaged software owned by marketers, serving marketers. Having looked at CDP’s as a band aid that fixes the proliferation of data silos that emerged for a number of reasons, I have ultimately come to the conclusion and am here to say that the customer data platform as an entity is increasingly becoming irrelevant – or in the typical marketing hyperbole – dead. Why is that? There are mainly four reasons for it. For one, many an application has its own CDP variant already embedded as part of enabling its core functionality. Any engagement solution that is worth a grain of salt needs the analytical capabilities that a CDP offers, and hence offers them itself. Why do the additional investment of buying things that one already has once more? This only increases cost and IT landscape complexity while acquiring capabilities that partially are already available. In addition, there is no real and concise definition anymore, with even the CDP Institute differentiating use types and/or scopes of CDPs. If you are looking at what other vendors (Salesforce, Oracle) or analysts (here: Gartner) are saying, the water becomes even more muddy. The...