Most companies think AI adoption starts with tools, chatbots, or agents. But real AI transformation starts somewhere much simpler: understanding how work actually gets done.

In this episode of Alt-Consulting: AI Adoption Conversations, Utsav speaks with Marvin Martinez, Founder and CEO of Bansor AI, about how small and mid-sized businesses can use AI and automation to eliminate manual work, reduce operational friction, and improve AI productivity.

Marvin shares practical examples of AI implementation across back-office workflows, logistics operations, lead generation, CRM updates, recruitment processes, and sales automation. The conversation shows why successful AI adoption is not just a technology problem. It is also a workflow design, consulting, AI change management, and organizational transformation challenge.

We discuss:

00:00 Introduction
01:26 Why SMBs are ideal for AI adoption
02:44 Automating back-office workflows
07:07 Why process clarity matters before AI implementation
08:29 AI-powered lead generation and CRM automation
15:12 Customizing automation for sales teams
19:32 Reducing errors in recruitment and onboarding workflows
24:42 AI change management and employee involvement
26:05 Final thoughts on AI adoption and transformation

Key takeaway: Don’t start with the AI tool. Start with the workflow. AI adoption works when organizations redesign processes, involve employees early, and use automation to free people for higher-value work.

If you are a business leader, founder, operator, consultant, or transformation leader working on AI adoption, AI transformation, AI productivity, or organizational change, this conversation offers a practical view of what actually works.

Subscribe to Alt-Consulting: AI Adoption Conversations for more discussions with AI adoption advisors, consultants, founders, and transformation leaders on how AI is changing work, consulting, and organizational transformation.

#AIAdoption #AITransformation #AIProductivity #AIChangeManagement #Consulting #OrganizationalTransformation #BusinessAutomation #AIAdoptionAdvisors #WorkflowAutomation #AltConsulting

This episode explores AI adoption, AI transformation, and why AI is not delivering results in many organizations. A key insight: AI adoption is not a technology problem, it is a behavior and culture problem.

Using lessons from Ritz-Carlton’s service excellence, this conversation breaks down how organizations can drive behavioral change for AI, build a strong execution culture, and move from AI pilots to real results.

The conversation dives into what it actually takes to drive organizational change for AI. It explores the role of leadership in shaping behavior, how culture is operationalized through hiring and corrective mechanisms, and why most AI initiatives fail without a shift in how people work.

Through the Ritz-Carlton example, the discussion highlights how service culture is designed, implemented, and sustained at scale, and what AI-driven organizations can learn from it. It also examines how companies can start the journey of AI transformation, drive customer-centric change, and sustain innovation over time.

If you are working on enterprise AI adoption, scaling AI beyond pilots, or trying to make AI deliver measurable business results, this episode offers a practical lens on what actually works.

• AI adoption is a behavior change problem, not a technology problem
• Leadership plays a critical role in driving organizational change for AI
• Culture systems determine whether AI transformation delivers results
• Service excellence principles can accelerate AI adoption at scale

00:00 AI Adoption and the Challenge of Behavior Change
05:58 Service Culture and AI Transformation: Ritz-Carlton Example
10:59 Starting Organizational Change for AI
19:52 Sustaining AI Transformation and Innovation
24:52 Behavioral Change for AI Adoption
30:58 Scaling AI Adoption Across Organizations

The conversation delves into the fundamental shift in consulting due to the impact of AI, leading to the emergence of Alt Consulting and the need to rethink work with AI. It explores the challenges and opportunities presented by this shift, providing insights into the future of consulting and work itself.

Takeaways

• Behavior change is the key challenge in adopting artificial intelligence
• The shift in consulting is a preview of how work itself is going to change

This episode explores AI adoption, AI transformation, and the rise of the Fractional Chief AI Officer as organizations struggle to turn AI investments into real results. As many companies face the challenge of AI not delivering results, the need for leadership that can bridge strategy, execution, and organizational change has never been greater.

The conversation breaks down when and why companies need a Chief AI Officer, and how the role is evolving from a niche leadership position to a critical driver of enterprise AI adoption. It examines the emergence of the Fractional Chief AI Officer model, especially for organizations that need senior AI leadership without committing to a full-time role.

The discussion also explores the role of CIOs in AI adoption, how responsibilities are shifting across leadership teams, and what it takes to drive AI transformation at scale. A structured, three-phased approach is outlined, along with a real-world case study, showing how organizations can move from fragmented AI initiatives to a more integrated and outcome-driven model.

The episode further examines whether the Chief AI Officer is a transitionary role or a long-term capability, and what CEOs need to consider when building leadership for AI. If you are leading AI strategy, working in AI consulting, or trying to scale AI beyond pilots, this conversation provides a practical view of how leadership drives results.

00:00 AI Adoption and the Rise of the Chief AI Officer
07:38 When Do You Need a Chief AI Officer?
16:10 AI Transformation Framework: A Three-Phased Approach
24:55 Fractional vs Full-Time Chief AI Officer

This episode explores AI adoption, AI transformation, and how they are reshaping the consulting future. As AI continues to evolve, it is not just changing tools and workflows, but fundamentally redefining how consulting delivers value and how organizations drive results.

The conversation examines how technological disruption and global economic shifts are accelerating the need for enterprise AI adoption, and why traditional consulting models are struggling to keep up. A key theme is the integration of AI at the source, where AI is embedded directly into how work is done, rather than layered on top of existing processes.

It explores how this shift is redefining AI consulting, changing the role of advisors from delivering recommendations to enabling execution and outcomes. The discussion also highlights why many organizations are investing in AI but still facing the challenge of AI not delivering results, and what this means for the future of advisory work.

The episode further dives into the challenges faced by traditional consulting firms, the emergence of new consulting models, and the biggest hurdles for up-and-coming firms trying to operate in an AI-driven world. If you are involved in AI transformation, rethinking your consulting strategy, or exploring how AI adoption is changing the role of consulting, this conversation provides a clear, forward-looking perspective.

• AI adoption is reshaping the consulting future and redefining how value is delivered
• Embedding AI at the source is critical for AI transformation at scale
• Traditional consulting models are challenged by the shift toward AI-driven execution
• The gap between AI investment and outcomes highlights why AI is not delivering results in many organizations

This episode explores AI adoption, AI transformation, and how organizations can move from strategy to execution in a world where AI is not delivering results for many companies.

In conversation with Siddharth Bohra, Founder of Trmeric, the discussion dives into how enterprises are rethinking AI consulting, AI strategy, and the role of technology leadership in driving real outcomes. A central theme is the gap between strategy and execution, and how most organizations struggle to translate ideas from presentations into tangible business impact.

Siddharth introduces the concept of an AI-native operating system for enterprise transformation, designed to bridge this gap. The conversation explores how embedding AI directly into workflows, decision-making, and execution processes can accelerate enterprise AI adoption and eliminate inefficiencies that slow down transformation.

The episode also examines the rise of “strategy as a product” and how AI is reshaping the consulting future, moving from slide-based recommendations to system-driven execution. It highlights how AI consulting models are evolving, and why the bar for value creation in consulting is rising rapidly.

A key focus is on the real blockers to AI adoption. From organizational readiness to ownership challenges, the discussion unpacks why AI adoption challenges persist and what it takes to overcome them. It also explores how leaders can drive organizational change for AI and behavioral change for AI, ensuring that technology investments translate into productivity improvement and revenue growth.

The conversation further covers:

• How AI can reduce wasted time and improve decision-making quality
• Why embedding AI into workflows is more powerful than layering it on top
• The evolving role of CIOs and technology leaders in AI transformation
• How teams can use AI to operate with greater purpose and business alignment

For builders, the episode offers practical insights on creating AI-native products, including the importance of solving real customer problems, applying systems thinking, and building integrated solutions rather than standalone AI features.

If you are working on AI adoption, leading AI transformation, building AI products, or rethinking the role of consulting in an AI-driven world, this episode provides a clear, practitioner-led perspective on what actually works and how to make AI deliver real results.

00:00 AI Adoption and the Strategy-to-Execution Gap
04:15 AI Transformation and the Rise of AI-Native Systems
10:30 AI Adoption Challenges and Organizational Readiness
18:30 Embedding AI into Workflows and Decision-Making
23:20 Building AI Products: Systems Thinking and Real Use Cases
30:20 AI Consulting and the Future of Strategy Execution

This episode explores AI adoption, AI consulting, and how AI transformation is reshaping the consulting industry from a people-driven model to a software-driven one.

In conversation with Alibek Dostiyarov, Co-founder and CEO of Perceptis AI, the discussion dives into the rise of “strategy as a product” and how AI-first platforms are enabling consulting firms to scale without proportionally increasing headcount. As organizations continue to invest in AI but face the challenge of AI not delivering results, new models are emerging that embed AI directly into consulting workflows.

A key theme is how traditional consulting, which historically scaled through people, is now beginning to scale through software. The episode examines how AI consulting is evolving, and why firms need to rethink how proposals, knowledge work, and client delivery are executed in an AI-driven world.

The conversation also explores how AI adoption challenges are being addressed through purpose-built tools like Perceptis, which act as an AI-native operating system for consulting firms. Instead of relying on generic tools, these systems embed AI into workflows such as proposal creation, slide building, and knowledge reuse, enabling faster and more consistent delivery.

Key topics covered include:

• How AI adoption is transforming consulting workflows and delivery models
• Why generic AI tools often fail in consulting due to trust and hallucination risks
• How AI can reduce manual work and improve productivity in consulting teams
• The role of proprietary data and firm-specific knowledge in differentiating AI outputs
• How boutique consulting firms can compete with larger firms using AI

The episode also highlights broader shifts in the consulting future, including the rise of boutique firms, fractional talent models, and AI-enabled specialists who can deliver more value with smaller teams.

For builders, there are practical insights on creating AI-native products, including the importance of solving real customer problems, ensuring data security, and applying systems thinking to build integrated solutions rather than standalone tools.

If you are working on AI adoption, leading AI transformation, building AI products, or rethinking the role of consulting in an AI-driven world, this episode provides a clear, practitioner-led perspective on how AI is changing both how consulting works and how organizations drive results.

00:00 AI Adoption and the Shift from People to Software
05:43 AI Consulting and the Rise of Strategy as a Product
11:00 AI Adoption Challenges: Trust, Data, and Differentiation
18:49 AI Operating Systems for Consulting Firms
22:27 Scaling AI Adoption in Consulting Workflows
25:28 The Future of AI Consulting and Boutique Firms

This episode explores AI adoption, AI transformation, and how consulting is evolving from a people-driven model to a system-driven one powered by autonomous AI.

In conversation with Jan Beránek, Founder and CEO of FifthRow, the discussion dives into how AI consulting is being reshaped by the rise of “services as software” and consulting as a product. As organizations continue to invest in AI but face the challenge of AI not delivering results, new models are emerging that embed AI directly into strategy, research, and execution workflows.

A central theme is how traditional consulting relied on teams of analysts and manual processes, while AI is now automating large parts of knowledge work. FifthRow’s approach of building an autonomous workforce using AI agents shows how organizations can move from slow, fragmented processes to always-on AI-driven systems that continuously generate insights, run analysis, and support decision-making.

The conversation explores how enterprise AI adoption requires not just new tools, but a complete redesign of processes, workflows, and organizational structures. It highlights why many companies struggle with AI adoption challenges, particularly around behavior change, trust, and integrating AI into day-to-day work.

Key topics covered include:

• How AI adoption is transforming consulting workflows and reducing reliance on manual analysis
• Why AI is not delivering results without process redesign and organizational change
• The rise of AI consulting platforms and autonomous AI agents
• How AI can move consulting from project-based work to continuous, always-on insights
• The role of data, fact-checking, and trust in scaling AI transformation

The episode also provides a behind-the-scenes view of building an AI-native company, including how FifthRow evolved through multiple iterations, adapted to rapid changes in AI capabilities, and shifted from a product platform to an outcome-driven consulting model.

A key insight is that while AI can automate analysis, human judgment, trust, and accountability remain critical, especially in high-stakes decision-making environments. The future of consulting may not eliminate humans, but it will fundamentally redefine their role.

For leaders, this episode offers a clear perspective on how to think about AI adoption at scale, how to redesign organizations for AI, and how to move from experimentation to real business impact.

If you are working on AI adoption, leading AI transformation, exploring new models of AI consulting, or rethinking how strategy work gets done in an AI-driven world, this episode provides a practical, forward-looking view on what is changing and what comes next.

00:00 AI Adoption and the Shift from Services to Software
04:33 AI Consulting and the Rise of Autonomous Systems
08:03 AI Transformation and Redesigning Workflows
15:00 Building AI Agents and Enterprise AI Adoption
20:22 AI Adoption Challenges and Behavior Change
29:28 The Future of AI Consulting and Autonomous Organizations