Advanced artificial intelligence never stops surprising the world. AI trends in the next three to five years are likely to centre around generative AI which is a white-hot technology. There will be more forms of GenAI in addition to the ones which generate texts, audio and video. In the future GenAI will be specialized GenAI to do specific tasks. It will be more efficient and more accessible. Machine learning or predictive AI which is a mature technology will be more precise and can be applied increasingly to support business decisions.

Despite the continuous development of AI, many organizations have not fully applied it. Bluebik Group Public Company Limited (BBIK), a leading consultancy on end-to-end digital transformation, takes the view that if organizations want to expand their AI adoption to effectively boost their business, they should start with an AI road map which covers data strategy and data governance. With data strategies, data can be used to achieve business goals. Meanwhile, data governance creates standards for efficient data management and use. This will be a basis for AI development as well as data and AI-driven cultures which promote skill development and the application of new technologies.

Bluebik believes that to successfully create an AI Roadmap, organizations should focus on and prepare for four key factors:

• Data

For AI implementation, organizations need to be well-prepared with their data. This starts with having consistent data collection guidelines and processes to ensure accurate, complete, and high-quality data. Effective data management and processing procedures are essential, along with comprehensive data usage governance.

• Technology

To utilize AI for complex tasks, organizations need a robust data management system (Data Platform) that consolidates data from various sources into a single location and processes it in real-time. Additionally, other systems that support AI integration into various processes, such as ERP, CRM, or HRMS systems, are also necessary.

• People

Organizations should have a team with the skills and understanding to use AI both from a business and technical perspective. This includes applying AI to various tasks, addressing AI limitations or impacts, and maintaining high-quality data for AI model training. To add business value through AI, having dedicated Data and AI experts to develop technology suitable for the organization is crucial.

• Policies and Processes

At a basic level, organizations should have policies and processes for the appropriate use of AI, particularly regarding data privacy and security. Users should be cautious not to disclose sensitive information when inputting commands for AI to generate results.

If organizations aim to use AI at a more complex level, beyond data privacy and security policies, data governance guidelines are needed to establish data management and oversight standards. Furthermore, stricter responsible AI usage guidelines should be in place to minimize biased or distorted outcomes and ensure the reliability of AI-generated results.

AI Adoption Maturity Framework

Business organizations should assess their AI adoption capabilities and Bluebik has developed AI Adoption Maturity Framework especially for this purpose. The framework can be applied for the assessment at four levels depending on the roles of AI users and the complexity of AI application.

Level 1 – Assisting: Greater Efficiency

AI enhances efficiency in general tasks and also speeds them up. Humans continue to play important roles and use AI solutions to serve their demand. For example, people use AI tools to gather data, write reports and generate pictures and video. In Level 1, AI is applied for general purposes and users do not need any special technical expertise.

Level 2 – Processing: Calculation and Processing

AI replaces humans at some extents. For example, they make calculation and process data but humans continue to order such application. At this level, organizations must have data readiness. Accurate data must be input for AI to process them precisely. Apart from data quality, users must know about AI limitations and be able to choose the right types of AI for relevant tasks.

Level 3 – Integrating: Integration into Organizations’ Systems to Automate Routine Tasks

AI takes over most tasks as humans designed. It is integrated into the operations of organizations and automates routine tasks. At this level of AI application, organizations must ready data for real-time processing and have a system for AI integration. As well, their personnel must have more technical knowledge about AI including software integration for the integration and correct functions of AI. They also need to be knowledgeable about AI customization to adapt AI to business operations.

Level 4 – Decision Making: Wiser Business Decisions Create Innovations

AI is applied to assist in decision-making, support strategy formulation and develop visions to further increase business value. AI can also create uniqueness and competitive edge. At this level, AI must be tailormade for each organization. For example, an in-house GenAI model can support the knowledge management of an organization by searching for and compile the data of the organization.

AI Road Map for AI Maturity

Bluebik has assessed AI adoption capabilities of organizations and found that many of them are using AI only at Levels 1 and 2. To reach higher levels, organizations should work out their AI road maps from their fundamental level. They can begin with improving their data which are vital for successful AI application. To have AI maturity, organizations need the following factors.   

• Data Strategy

Data strategy is the first and foremost step towards the development of AI to support business. With strong data strategies, organizations can develop their business potential in the long term. To plan data strategies, organizations should have clear goals and objectives of their AI application. They must know exactly which parts of their business should have AI support. Moreover, organizations must generate relevant use cases for their AI application to accomplish different objectives. 

• Data Governance

Organizations must prioritize data standards. Data governance creates standards for efficient data management as it covers directions and controls to guarantee data quality. Basically, data governance consists of three main parts: 1) data policy, 2) data governance team and 3) process.

            If organizations plan to apply AI to support more complicated tasks, they should have guidelines for AI application with greater responsibility to reduce the risks of distorted or prejudiced outcomes. Also, they should have methods to validate AI-generated results. 

• Data & AI-Driven Culture   

The last factor to ensure successful AI application concerns humans because they are AI users. Business organizations need the cultures that welcome their personnel to have and use new technologies. They should organize training to continuously improve the knowledge, skills and capabilities of their personnel so that their people can fully apply AI to meet their objectives. As well, organizations should measure their own data and AI readiness by conducting data & AI capability assessment.

To Bluebik, another crucial factor behind successful efforts to develop AI maturity is the role of high-level executives (the C-suite) who are responsible for different areas of management.

• Chief Executive Officer (CEO) and Chief Financial Officer (CFO) 

The important role of CEOs is to make decisions on AI strategies and transformation road maps which will lead to the long-term development of AI application capabilities at their organizations. Meanwhile, CFOs are duty-bound to ensure that investments in AI technologies will be very beneficial to their organizations.

• Chief Operating Officer (COO)

COOs work out policies and processes for suitable and optimal AI application. 

• Chief Technology Officer (CTO)

CTOs oversee technology in particular. Their responsibilities cover the formulation of policies and guidelines for data and AI governance as well as the development of data platforms and AI models that suit their organizations.

• Chief People Officer (CPO)

CPOs supervise personnel development intended to enable staff to apply AI to boost efficiency. CPOs develop new skills and push for the organizational cultures that embrace technologies.

In the future, advanced AI will help unlock business potential in unconventional manners. Existing technologies will be further developed into the innovations that raise business value. From Bluebik’s point of view, the organizations that quickly apply technologies can certainly create competitiveness and new business opportunities and achieve steady growth. Regarding the complexity of AI technologies, consultation with external experts is another major factor to help organizations transform themselves continuously and achieve long-term growth.

To serve the business organizations that need AI strategies to boost their competitive edge and stimulate growth, Bluebik has teams of experts who master big data and advanced analytics and are ready to present end-to-end solutions and apply advanced analytics to support strategy formulation and effective implementation. We are always pleased to answer questions and provide consultation at ✉ [email protected] and ☎ 02-636-7011