Artificial Intelligence (AI) has become an increasingly popular topic in recent years, with many organizations looking to leverage its power to improve their operations and drive success. However, understanding the differences between GenAI and the more advanced SAI (Strategic AI) is crucial for those new to the AI world.

While AI has existed for some time, and many products are based on ChatGPT or similar, SAI represents a significant leap forward in how organizations can use AI to drive strategic success. Strategic Future AI is presenting the first SAI in the world.

This section will introduce you to two key concepts: traditional AI (or GenAI) and Strategic AI (SAI). We will explore the differences between these two types of AI and how they can be applied in a business context. By the end of this article, you'll understand how SAI, like Hanna Prodigy, can help your organization achieve its goals and drive strategic success.

What is GenAI?

GenAI or Generative AI is a class of artificial intelligence models designed to generate new content based on patterns learned from existing data. Unlike AI, which primarily focuses on recognizing patterns and making predictions, Generative AI creates novel outputs that resemble the data it was trained on.

GenAI is also designed to perform specific tasks or answer specific questions. It operates flat and one-dimensional, meaning it doesn't consider an organization's broader context, structures, hierarchies, or information flow in the company.

Think of GenAI as a digital encyclopedia. You can ask it a question, and it will provide you with an answer based on the information it has been programmed with. For example, you might ask a GenAI system, "What is Business Agility, and how can it impact my team?" It will respond with some answer depending on the model and power.

While GenAI can be useful for certain tasks, such as automating repetitive processes or providing quick answers to questions, it also has limitations. It doesn't understand your business's specific needs, goals, or structures, how they cascade down, or how information flows across the organization. It can't provide insights or recommendations tailored to your specific context where business structures and power might influence rules and knowledge scope.

What is Strategic AI (SAI)?

Strategic AI, or SAI, is a more advanced artificial intelligence engine designed to align with your organization's needs, goals, and knowledge flow. Unlike GenAI, which operates on a flat, one-dimensional level, SAI is a multilevel system that can understand and adapt to your organization's unique structure.

SAI is currently offered by Hanna Prodigy, the only provider in the world at the moment. Hanna is trained to understand the specific context and structures of each department or team in your organization and how they interact and contribute to the overall business strategy. This means that SAI can provide insights and recommendations tailored to the needs of every level of your organization, from individual team members to department heads to senior management.

SAI (c) Strategic Future AI and Erich R. Bühler

For example, let's say your company has a marketing department, a sales department, a finance department, and a human resources department. Each department has its own unique goals, processes, and knowledge base. With SAI, you can train the AI to understand each department's specific needs and requirements and how they fit into the broader organizational structure.

SAI can be trained at the whole company, initiative or team, and private levels. When a person asks an AI a question, these levels influence each other, and the AI dynamically provides an answer based on the person's position in the company.

This allows SAI to provide a person or initiative with relevant and actionable insights and recommendations. For example, SAI might analyze customer data from the marketing department to identify trends and preferences and then recommend to the sales department how to tailor their approach to better meet customer needs. At the same time, SAI might provide insights to the finance department on how to optimize budgets based on the performance of marketing and sales initiatives.

SAI's Multi-Level Training: Tailoring AI to Your Organization's Structure

One key feature that sets Strategic AI (SAI) apart from GenAI is its ability to be trained at multiple organizational levels. This multi-level training approach allows SAI to adapt to your company's unique structure and needs, providing tailored insights and recommendations that are relevant and actionable at every level. Let's break down the three main levels at which SAI can be trained:

1. Company Level: When SAI is trained at the company level, it learns about the overall goals, strategies, and objectives of your organization. This high-level training allows SAI to understand the big picture and provide insights aligned with your company's direction. This means training at this level will influence all initiatives.
   
2. Initiative or Team Level: SAI can also be trained at the level of specific initiatives or teams within your organization. This allows the AI to understand each team's unique goals, challenges, and processes and provide insights tailored to their needs.
   
3. Private Level: SAI can be trained at the individual or private level, learning about each team member's roles, responsibilities, and goals. This personal-level training allows SAI to provide customized support and recommendations relevant to each individual's unique needs and challenges.

What sets SAI apart is its ability to provide dynamic, multi-level insights considering the person's role and position within the organization. When someone asks SAI a question, the AI does not rely on a single level of training to provide an answer—as AI would. Instead, it considers the relevant insights from all levels of training and provides a comprehensive and customized answer.

By providing dynamic, multi-level insights, SAI empowers individuals and teams to make informed, data-driven decisions that align with the broader organizational context. This holistic approach to AI-driven decision support makes SAI an indispensable tool for organizations looking to drive strategic success at all levels.

The Three Pillars of SAI

Strategic AI (SAI, as Hanna Prodify) is a groundbreaking approach to artificial intelligence that aims to revolutionize how companies use AI to transform and succeed.

SAI (c) Strategic Future AI and Erich R. Bühler

SAI is based on three key characteristics that differentiate it from traditional AI and enable it to deliver unparalleled value to organizations:

1. Multi-level architecture: Aligning AI to your organizational structure
   One of the biggest limitations of GenAI is its flat, one-dimensional structure. It treats information as monolithic entities and doesn't consider the complex hierarchies, power, teams, and individuals that make up a company. In contrast, SAI relies on a multi-level architecture that reflects your organization's structure and knowledge flow. By training SAI at the company, initiative or team, and private levels, you can ensure that the AI understands the unique goals, challenges, and dynamics of each level of your organization. With SAI's multi-level architecture, you can break down silos, foster collaboration and drive strategic alignment across your entire organization - from the executive suite to frontline employees.
   
2. Parallel language processing: overcoming language barriers
   Language barriers can hinder effective collaboration and knowledge sharing in today's globalized business world. SAI tackles this challenge head-on with its parallel language processing capability. SAI can be trained in multiple languages simultaneously. This means that team members can interact with SAI in their native language while benefiting from the collective knowledge and insights of the entire organization. SAI's parallel language processing enables seamless cross-cultural collaboration, allowing team members to share ideas, insights, and best practices regardless of their language background.
   
3. Anthropomorphic design: fostering empathy and understanding
   Organizational change is a complex and often emotional process that requires a deep understanding of human dynamics and behavior. SAI's anthropomorphic design enables a more natural, empathetic interaction with employees, fostering trust and understanding. By embodying human-like qualities such as empathy, emotional intelligence, and contextual awareness, SAI can better understand your organization's unique challenges and opportunities. It can connect with employees more personally, providing support, guidance, and motivation tailored to their individual needs and preferences. The SAI's anthropomorphic design also allows Hanna to support better decisions. By modeling the desired behaviors and values, SAI can help drive cultural change and foster a shared vision for success.

The three pillars of strategic AI—multi-level architecture, parallel language processing, and anthropomorphic design, represent a paradigm shift in how organizations use AI to succeed.

SAI is also supported by a new financial model that helps organizations deal with the new, accelerated reality. This model is called the TriValue Company Model or TVC. We will explain it below.

The Benefits of SAI for Company Change

By leveraging the power of SAI, organizations can drive strategic success and achieve their goals more effectively. Some of the key benefits of SAI include:

1. Tailored Insights and Recommendations: SAI provides insights and recommendations tailored to the specific needs and goals of each level of your organization, from individual team members to executive leadership.
   
2. Improved Collaboration and Knowledge Sharing: SAI can help break down silos between departments and teams, facilitating better collaboration and knowledge sharing across the organization.
   
3. Enhanced Decision-Making: With SAI, organizations can make more informed, data-driven decisions aligned with their overall strategy and goals.
   
4. Increased Efficiency and Productivity: By automating certain tasks and processes, SAI can help organizations operate more efficiently and productively, freeing up time for people for higher-level strategic initiatives.

As you can see, SAI is the next generation of AI in organizations. It can accelerate transformation and change because SAI is trained with Enterprise Agility's latest frameworks and financial models.

Fitting to your Organizational Structure

Let's say your company has a hierarchical structure with different departments, such as marketing, sales, finance, and human resources. Each department has its own goals, processes, and knowledge base. SAI can be trained to understand each department's specific context and requirements and how they interact and contribute to the overall company strategy.

Training at the Organizational Level

At the top level, SAI can provide insights and recommendations to executives and decision-makers, helping them make informed strategic decisions based on a holistic view of the organization. This could include identifying market trends, analyzing competitor strategies, or predicting future growth opportunities.

Company-level training enables SAI to align its insights and recommendations with its overall strategic objectives. By training AI at the company level, you influence all teams and initiatives across the organization.

Training at the Team or Initiative Level

SAI can offer tailored support and guidance at the initiative or team level. For example, in the marketing department, SAI can analyze customer data, provide insights on campaign performance, and suggest optimization strategies. In the sales department, SAI can help identify high-value leads, recommend personalized sales approaches, and forecast sales pipelines.

In a software, product, or agile team, SAI can provide invaluable support and guidance to enhance productivity, streamline processes, and drive innovation.

In product management, SAI can assist in gathering and analyzing customer feedback, identifying market trends, and prioritizing product features. It can help product managers make data-driven decisions by providing insights into user behavior, feature adoption, and customer sentiment. SAI can also facilitate collaboration between product teams and other departments, such as marketing and sales, ensuring that product decisions align with overall business objectives.

SAI can support agile teams' entire lifecycle, from sprint planning to retrospectives. It can analyze past sprint data, identify bottlenecks or inefficiencies, and recommend improvements to the agile process. SAI can also help estimate user stories, predict sprint outcomes, and optimize resource allocation. By providing real-time insights and recommendations, SAI empowers agile teams to continuously improve their processes and deliver value to customers more effectively.

SAI can also facilitate cross-departmental collaboration and company alignment (Strategic Alignment) by identifying knowledge gaps and ensuring that relevant information is shared effectively across all teams. For example, if the marketing team gains valuable insights about customer preferences, SAI can ensure that this knowledge is communicated to the product development team to inform future product decisions.

Training at the Personal level

At the individual level, SAI can provide personalized support and recommendations based on an employee's role, responsibilities, and goals. This could include suggesting relevant training materials, identifying potential process improvements, or offering guidance on specific tasks or challenges.

At the individual level, SAI can provide personalized support and recommendations based on an employee's role, responsibilities, and goals. By training SAI with data specific to each employee, organizations can unlock a new level of personalized assistance that empowers individuals to excel in their roles and drive their own professional development.

Aligning Your Company and Knowledge Flow with SAI

By aligning with your company's structure and providing tailored insights at every level, SAI ensures that the right information reaches the right people at the right time. This enables your organization to make informed decisions, adapt quickly to changes, and drive strategic success in a way that GenAI cannot match.

At the top level, SAI can provide insights and recommendations to executives and decision-makers, helping them make informed strategic decisions based on a holistic view of the organization. This could include identifying market trends, analyzing competitor strategies, or predicting future growth opportunities.

SAI can offer tailored support and guidance at the initiative or team level. For instance, in the marketing department, SAI can analyze customer data, provide insights on campaign performance, and suggest optimization strategies. In the sales department, SAI can help identify high-value leads, recommend personalized sales approaches, and forecast sales pipelines.

SAI can also facilitate cross-departmental collaboration by identifying knowledge gaps and ensuring that relevant information is shared effectively. For example, if the marketing team gains valuable insights about customer preferences, SAI can ensure that this knowledge is communicated to the product development team to inform future product decisions.

At the individual level, SAI can provide personalized support and recommendations based on an employee's role, responsibilities, and goals. This could include suggesting relevant training materials, identifying potential process improvements, or offering guidance on specific tasks or projects.

Parallel Language: Enabling Multilingual Collaboration with SAI

The international workforce often has individuals who speak different languages. This linguistic diversity can sometimes create barriers to effective collaboration and knowledge sharing. However, with SAI's parallel language capability, organizations can overcome these challenges and reap the benefits of multilingual collaboration.

SAI supports multilingual training and allows users to train AI in their native language, even within the same organizational level. This means team members can enter information for training, documents, and insights into their preferred language without translating. SAI processes and integrates this multilingual information into its knowledge base, creating a unified understanding of the team's collective knowledge.

Take, for example, a team in which half the members speak Spanish and the other half English. With SAI's parallel language capability, both subgroups can train Hanna Prodigy in their respective languages. The Spanish-speaking members can enter initiative updates, meeting notes, and any other feedback in Spanish, while the English-speaking members can do the same in English.

When an initiative member asks SAI about their performance or project status, regardless of their language, the AI draws on the collective knowledge it has absorbed in both languages to provide a comprehensive answer. SAI does not simply translate the information but transforms the user's knowledge into its own unified understanding and can offer insights and recommendations that leverage the team's collective expertise.

This parallel language capability is crucial for cross-functional teams that span different regions or countries. For example, a global marketing team may have members with various linguistic backgrounds, each bringing unique market insights and customer perspectives. By training these team members on SAI in their native language, they can ensure that their local knowledge is fully captured and integrated into AI's understanding of the global market landscape.

The Power of a New Financial Operating System for Companies

SAI, like Hanna Prodigy, is focused on providing leaders and consultants with the insights, guidance and support they need to succeed in the face of uncertainty and change. One of the key benefits of SAI for leaders and consultants is its ability to provide a holistic, strategic perspective on organizational challenges and opportunities. While SAI's multi-level architecture makes it possible to understand and analyze the complex interplay between the different levels of the organization, the TriValue Company Model (TVC) helps the organization to deal financially with the new reality.

What is the TriValue Company Model (TVC)?

The TriValue Company Model is a strategic framework that helps organizations align the value of customers, business and workforce. It promotes healthy company alignment, collaboration and the ability to find new opportunities in the new reality.

In companies exposed to accelerated change and exponential markets, a narrow focus on customer value alone may not be enough to ensure long-term success. While customer centricity is still essential, the rapid pace of change and the complexity of these markets require a more balanced approach that considers the needs of the business and its workforce.

The pressure to innovate and adapt quickly can be intense in exponential markets. Companies that prioritize customer value can make short-term decisions that undermine their long-term viability. For example, a company may rush to bring a new product to market to meet customer demand, overlooking critical issues related to production costs, employee training or pressure, or strategic direction. As a result, the company may struggle to maintain profitability, retain talented employees, or adapt to future market changes.

In addition, customer needs and preferences can change rapidly in fast-moving markets. A company that focuses too much on satisfying the needs of its current customers may fail to anticipate or adapt to emerging trends and opportunities. This leaves the company vulnerable to disruption from more agile competitors who are better able to innovate and respond to changing market conditions.

To succeed in this challenging environment, companies need to strike a balance between value for customers, value for the business and value for the wellbeing of the workforce. By taking a holistic view of value creation, companies can make strategic decisions that position them for long-term success. This may include investing in new technologies or business models that allow for greater agility and adaptability, even if they don't maximize customer value immediately. It may also mean prioritizing employee development and engagement to ensure the company has the necessary skills and expertise to meet future challenges.

The TriValue Company Model provides a framework to achieve this balance. By considering all three types of value – customer, company and workforce – the TVC model enables companies to make more informed strategic decisions that take into account the complex interplay between these different stakeholders. This approach is particularly valuable in exponential markets, where the ability to adapt quickly and make smart, data-driven decisions is critical to survival and growth.

SAI's integration of the TVC model is particularly valuable for executives and consultants. By providing insights and recommendations that consider all three types of values, SAI enables leaders and consultants to make more balanced and effective decisions.

SAI: Fostering Neurodiversity, Inclusion, and Financial Success

SAI also helps bridge this gap by providing personalized support and adjustments for neurodiverse employees. By analyzing individual communication styles, learning preferences, and work patterns, SAI can be set at the initiative level to offer tailored recommendations and adjustments that enable neurodiverse people to perform at their best. This may include suggestions for alternative communication channels, visual aids or structured task lists, or identifying opportunities for skills development and career progression.

SAI's integration of the TriValue Company model (TVC) highlights the financial benefits of neurodiversity and inclusion. The TVC model balances value to the customer, the company, and the workforce's wellbeing, recognizing that all three areas are interconnected and important for long-term success.

When organizations prioritize the wellbeing of their employees—including the needs of neurodiverse employees—they can create a more engaged, productive and loyal workforce, which in turn leads to better outcomes for customers and the organization as a whole during accelerated change.

Ancient Knowledge Applied to AI

"SAI" (歳) means "prodigy" in Japanese, emphasizing AI's advanced capabilities and potential for strategic purposes.

Embracing SAI, like Hanna Prodigy, means unlocking the full potential of AI-driven strategic collaboration. It's not just about having access to information; it's about having an AI system that understands your organization, adapts to your needs, and provides actionable insights to drive your company forward.