AI is becoming more prevalent in everyday situations like identifying fraudulent activities in financial services, predicting retail purchases, and facilitating online customer support. Although it is becoming more influential in informing business decisions, it can be misused if leaders cling to outdated decision-making approaches. A crucial aspect of successful teamwork involves acknowledging which aspects of a problem are best suited for AI to handle and which are better addressed by human thinking.

The variety of AI consulting engagements can target different problems depending on the maturity of the business regarding AI and the outcomes you want to achieve. The spectrum of services starts with engineering plans for first-time adoption, performing AI audits or strategy expansion and user trainings. Other types of problems to solve include building proof-of-concept for AI models, AI in the cloud infrastructure setup or long-term data management.

To create tailored AI solutions, data scientists must train algorithms on diverse sets of data, including images, text, and specific information like financial transactions or viewed products. They can acquire data through prepackaged options or public crowdsourcing and should ensure their dataset includes positive and negative examples for learning. Our AI consultants and data scientists experiment with different algorithms and utilize a test set to evaluate and improve the AI models.

Before investing in new technology, every business should ask themselves what form does the expected return take and design for specific ways to measure the actual outcome. You might be looking for improved decision-making through AI-driven insights, increased operational efficiency and cost savings or gaining competitive advantage through AI adoption. AI consulting can help you set your expectations right and plan for the result that would have the highest impact for your business. Be it growth, differentiation or performance-related, practical AI can help you get to the desired change faster and more efficiently.

AI development requires a range of specialists with complementary skills, including data scientists, ML and software engineers, etc. Key skills also include programming, statistics, machine learning frameworks, big data, and distributed systems. The exact composition of the team will depend on the specific goals of your project and the resources available. It's important to identify the necessary roles and skills early on and to build a diverse team with complementary expertise.

The costs for AI development can vary depending on the scope and complexity of the project. Factors that are considered include the type of AI technology used, the amount of data required for training, the complexity of the algorithms, the size of the development team, and the duration of the project. However, with Accedia, clients can benefit from tested and ready-to-use AI models that reduce costs and development time.