With the decline in hype about AI developments (especially LLMs like ChatGPT), the implementation of AI in many industries will again make stakeholders aware of the need to do their homework again.
What is that homework?
Implementing all the latest technological developments cannot be separated from the three pillars, namely People, Process, and Technology. We can see here that technology is only one of three main components. As long as the other two components are not upgraded, no matter how much investment is made, it will not have an impact on the company’s profit or revenue.
People – The Main Pillar of Every Organization
This is the most important component. Does every individual understand the impact of AI implementation on their work? It is necessary to provide a comprehensive understanding that the implementation of new technology will make their work easier and not replace workers. In fact, AI will help do repetitive and boring work so that workers can use their working hours to think about more strategic things.
Example: AI can help draft letters (or emails) based on thousands of official letters from the company so that the choice of words and the arrangement of sentences can follow the style of the company. In the retail context, for example, AI can personalize the customer shopping experience, while in the manufacturing sector, AI can be used for predictive maintenance that reduces machine downtime.
However, this only applies to companies with a passion for continuously improving the quality of the products and services they produce. Therefore, companies need to focus on training, technology literacy programs, and open communication so that each individual feels supported, not threatened.
Process – The Importance of Having an Adaptable System
This part is the most difficult challenge to implement, especially in large companies with a large number of employees. The many internal procedures that are already in place and the risk of failure make implementing new technology more complex.
Progressive companies usually start changes on a small scale (pilot projects) and monitor the results regularly. For example, a fintech company can test AI to detect fraud in small transactions before expanding its use to the entire system.
This process takes quite a long time (3-5 years) so it is very important to maintain expectations. In addition, the steps of change must include:
- Training Program: Providing training to employees on new procedures.
- Change Management: Building a dedicated team tasked with managing the transition and overcoming employee resistance.
- Monitoring & Feedback: Routinely measuring the effectiveness of change with clear KPIs.
Technology – Implement Technology After Having Clear Business Targets
If the company is not engaged in technology, it is very important to have adequate resources to implement AI effectively. This can be done by:
- Structured Recruitment: Forming an internal AI team gradually to ensure that knowledge related to AI can be owned by the company.
- Collaboration with Third Parties: Collaborating with consultants or technology vendors to accelerate implementation while conducting knowledge transfer.
Examples of technology applications:
- Banking: Using AI for customer segmentation or fraud detection.
- Logistics: AI for shipping route optimization.
- Smart City: AI in traffic management.
In addition, it is important to ensure that the technology adopted has high scalability and can adapt to future developments.
Emerging Trends in AI
Moving into 2025, some AI trends worth anticipating are
- Generative AI: Utilizing technology to create content more than text, such as images, sound or videos.
- AI at Edge Computing: Enabling real-time data processing in mobile device without reliance on the cloud.
- Autonomous Systems: Development of autonomous systems such as driverless vehicles.
This trend opens up new opportunities, but also requires readiness in three main pillars.
Ethical Considerations in AI
As AI adoption increases, ethical issues such as algorithm bias, transparency, and data privacy become increasingly crucial. Companies must ensure that:
- The data used is free from bias.
- The AI decision-making process is transparent and explainable.
- Customer privacy is protected according to applicable regulations.
Measuring AI Success
The success of AI implementation must be measured by clear KPIs, such as:
- Process Efficiency: Is the process faster or cheaper?
- Revenue Increase: Does AI have a direct impact on revenue growth?
- Customer Satisfaction: Do customers feel an increase in service quality?
Closing
These three concepts – People, Process, and Technology – will continue to be relevant, regardless of future technological developments. Collaboration across divisions is essential, and the board of directors must fully support any changes required for the long-term sustainability of the company.
As a first step, companies can conduct an AI readiness audit or hold cross-divisional workshops to identify opportunities for AI implementation. With a strategic approach, AI can be a powerful tool to drive innovation and business growth in 2025.
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