Latest

CIO: How to maximize the value of your AI strategy?

Share this post

CIO: How to maximize the value of your AI strategy?

AI is revolutionizing every sector, but one question remains: how can you maximize the value of your AI strategy while overcoming its challenges?

During its October 2024 IT Symposium, Gartner presented a study conducted in Q2 2024 with 451 senior technology executives in the EMEA region (Europe, Middle East, and Africa). The study revealed that 45% of CIOs (Chief Information Officers) are now tasked with driving an AI strategy within their organization.

However, major obstacles such as:

  • Technological complexity;
  • Cost management;
  • Ethical concerns;
  • Lack of skills;
  • Environmental impact;
  • Change management

make it challenging to create value with AI.

At Iguana Solutions,  Full Stack AI Platform helps companies to address these challenges by offering a turnkey platform designed to maximize the value of AI.

 

Simplifying Technological Complexity

 

The Problem:

Implementing AI, particularly generative AI, requires a deep understanding of technologies, seamless integration with existing systems, and algorithm bias management.

  • Rapidly evolving technologies: AI is often considered the Holy Grail, but its fast-paced evolution can lead to relentless innovation and sometimes disappointing results due to poorly calibrated models or unrealistic expectations.
  • Integration challenges: Incorporating AI solutions into complex IT environments requires careful planning and often heavy adjustments to ensure interoperability and operational continuity.
  • Relialibility of results: Algorithmic biases or hallucinations can compromise the relevance of generated responses.

With Full Stack AI Platform:

  • Benefit from a fully managed platform by Iguana Solutions experts, simplifying AI adoption for your teams.
  • Smooth, immediate integration via Kubernetes, compatible with all types of IT environments.
  • From language models to image generation, it’s easy to deploy and test your Proofs of Concept (PoCs), enabling the design of tailored products and solutions.

 

Managing Costs and Maximizing Profitability


The Problem:
AI is expensive, and its budget can be hard to forecast. A Gartner survey reveals that over 90% of CIOs see budget management as a major hindrance to AI valuation. According to Gartner, CIOss could make errors of 500% to 1,000% in cost estimates.
“You need to understand cost components and pricing model options and know how to reduce these costs and negotiate with providers. CIOs must create proofs of concept that test cost evolution, not just technology functionality.”- Daryl Plummer, Distinguished VP Analyst, Chief Research at Gartner

  • Budget complexity: Companies struggle to evaluate cost components, such as GPU resources, software licenses, or necessary adjustments to optimize model performance.
  • Uncertain profitability: Organizations find it difficult to quantify AI gains in terms of productivity or customer satisfaction.

Yet, according to a Gartner survey of over 5,000 digital workers across five countries (UK, US, India, Australia, China), employees save an average of 3.37 hours per week thanks to generative AI tools, translating to an almost 10% productivity boost. By changing certain approaches, businesses can use AI to deliver more value to their customers and increase revenue.

 

With Full Stack AI Platform:

  • Transparent, simple billing based on your GPU capacity needs, enabling clear cost anticipation.
  • Ongoing support to ensure your AI profitability goals are met for your business and/or clients.

 

Ensuring Ethics and Data Security

 

The Problem:
AI data usage raises growing concerns about ethics, security, and compliance.

  • Loss of data control: SaaS solutions and “on-demand” cloud models make it difficult to control the information transmitted to AI, increasing risks of cybersecurity breaches, information confidentiality, or regulatory non-compliance, such as GDPR.
  • Algorithmic biases: Depending on datasets and training methods that are not always accessible, AI models may reproduce or amplify biases, compromising decision quality.

 

With Full Stack AI Platform:

  • Open-source, auditable, and transparent models that allow you to know the methodology and data used for training.
  • Complete isolation of client environments, ensuring data security and preventing unauthorized use.
  • Implementation of RAG (Retrieval-Augmented Generation) to reduce hallucination risks and enhance response relevance in your company’s context.

 

CIO: How to maximize the value of your AI strategy?

Facilitating Access to Skills


The Problem:
Generative AI adoption requires experts in Machine Learning (ML), data management, complex infrastructure handling, and artificial intelligence. However, these talents are rare and expensive.

  • Training and recruitment: Companies must invest in training programs for their IT teams or recruit specialized talent, which can be costly and time-consuming.
  • Steep learning curve: Unprepared teams may struggle to fully leverage AI.

With Full Stack AI Platform:

  • A managed platform, reducing your need for specialized resources to just those essential for your domain of application.
  • A turnkey solution allowing you to focus on leveraging AI to enhance your business instead of spending time on operational aspects.

 

Managing and Monitoring Environmental Impact


The Problem:
Running AI models, especially large language models, consumes vast computing resources, potentially harming companies’ sustainability goals.

  • High energy consumption: AI models require powerful GPUs that consume more energy than standard servers.
  • Lack of transparency: Companies struggle to assess their AI-related environmental impact.

With Full Stack AI Platform:

  • Optimized infrastructure using next-generation GPUs like Nvidia H200, 50% more efficient than Nvidia H100.
  • Integrated dashboards in our Metrology to track energy consumption and CO₂ emissions, enabling real-time calculation of your AI usage’s environmental impact.

 

Driving Change and Improving Adoption

The Problem:
AI integration can cause employee concerns, ranging from apprehension about the unknown to fear of being replaced by machines.

  • Lack of buy-in: According to Daryl Plummer, “Gains vary among employees, depending not only on their personal interest and adoption level but also on the complexity of their roles and their experience level.”
  • Poor communication: AI is sometimes seen as a replacement rather than a support tool.

AI should be viewed as a tool to assist employees, not a universal solution to replace them. AI adoption must be accompanied by tailored training and support strategies that highlight its benefits while addressing individual concerns.

With Full Stack AI Platform:

  • An integrated AI AppStore offering ready-to-use applications to accelerate team adoption.
  • Tools designed to boost productivity and improve working conditions, rather than replace employees.

 

In Conclusion


As we’ve seen, artificial intelligence presents an unprecedented opportunity for CIOs to innovate and transform organizations. However, its deployment comes with significant challenges.

With Iguana Solutions’ Full Stack AI Platform, CIOs have a custom tool to overcome these obstacles. By simplifying deployments, optimizing costs, securing data, and facilitating adoption, we help you turn challenges into strategic opportunities.

In the end, AI should not be a technological headache but a value-creation lever for your employees, customers, and business. And that’s precisely what we offer with Full Stack AI Platform.

Share on Facebook

Iguane Solutions

Content Writer, Iguana Solutions

The know-how of Iguana Solutions allowed us to be relevant in our technical choices from the beginning of the project, while implementing exceptional economic efficiency.”

Jean-David Blanc

CEO, Molotov.tv (Acquired by Fubo.tv)

Get the Latest Updates

Stay informed with our latest blog posts and industry insights.