- The efficiency strategy
Most people think automation is the first thing that comes to their minds when they think about AI. However, AI has many other applications apart from automation. Despite this, the efficiency strategy is more about automation. It can be used for activities that have clearly defined rules and routines. Companies that adopt the efficiency strategy to optimize their processes do so with the intention of reducing costs. For example, with the taxi industry at risk of becoming fully automated soon, self-driving cars are increasingly becoming better than humans. Clearly defined rules for driving a vehicle are in place. Furthermore, fraud detection has been automated. As most routines are being discovered, automation algorithms are also becoming sophisticated.
- Effectiveness strategy
This strategy revolves around using AI to enhance the communication and coordination of workers. Here, AI takes the role of an assistant. This strategy is to make humans effective by eliminating or simplifying the act of scheduling, monitoring and communicating. Due to the rise of chatbots, it has become normal for companies to implement basic AI solutions with this strategy. You can also deploy this strategy for more complex activities. For instance, AI can be used to schedule meetings between workers. In large consultancy firms, AI can be deployed to suggest which person can be assigned a project based on employees’ skills, experience and desires. Apps built for services like Google Assistant, Alexa and Siri are some of the services in this category. With the rising number of people owning smart devices such as speakers, products built on effectiveness strategy have become important for customer-focused companies.
- Expert strategy
Unlike the two strategies above, this strategy is closely associated with augmentation. Expert strategy can help elevate human decision-making for activities containing complex work processes. While systems help in making decisions, humans have the final say. They can help in almost everything, from human lives to money matters. With the sensitivity of these areas, humans must always be responsible for the consequences of their decisions. The systems using this strategy empower professionals in different industries, such as lawyers, doctors, financial advisors and teachers, among other individuals, through advice. For example, AI solutions can help teachers create tests for individual students and evaluate them accordingly.
- Innovation strategy
This is the most advanced of all AI strategies. It is the opposite of the efficiency strategy and revolves around augmenting humans to enhance creativity. For example, a music composer can use software to create a new song. This can be done through a machine learning algorithm which learns the composer’s style of music by observing how he adds piano, guitar, bass or other musical instruments. The composer can then listen to the AI and decide whether it can be added to the song or not. With the decision of the composer, the AI can also learn and improve itself for the future. Like the expert strategy, the innovation strategy gives humans the final say in decision-making.
