Capable of deriving insights from large volumes of data, AI is being utilised to sport trends and opportunities far faster than human teams could achieve.
AI tools are also able to automate growing numbers of business processes. This allows staff to focus on more value-adding activities while allowing the AI tools to undertake the repetitive, mundane tasks.
The tools are also able to assist in the area of research and development. By analysing large data sets and results, the tools allow the pace of research projects to be increased without having a detrimental impact on the final results. This can lead to getting new innovations and products to market faster than has previously been possible.
The types of data sets that can be analysed by AI tools are many and varied. They include everything from customer and sales data to sensor data, social media posts and behavioural data to name but a few. On the technical front, analysis of IT logs and ops data can provide IT teams with new insights into how an organisation’s infrastructure is performing and what impact any planned or unplanned changes might have.
Embarking on a project
Asking how much a new AI-based project is going to cost is a bit like asking how long is a piece of string. In essence, it depends on the scenario and the problem the project team is looking to solve.
For example, if a decision is taken to opt for an out-of-box solution, such as a website chatbot, the cost will be relatively low. These AI-powered tools are relatively easy to deploy and have low ongoing operational costs.
However, as you shift to more sophisticated and customisable chatbots, there will be an increase in the cost of the technology as well as the implementation complexity and upkeep.
It’s important to understand, however, that AI should not be the exclusive domain of larger enterprises or expert users. Increasingly, AI technology is coming to market like The AI & Analytics Engine that seeks to democratise access through technological affordability and simplification.
Depending on the scenario and the problem being tackled, the size of the organisation should not matter. The team should be able to access the power of AI if they have a problem best solved with AI and data to solve it.
Formulating a readiness checklist
Before any investment is made in AI tools and projects begun, it’s important to carefully assess a range of factors. Together these factors can be thought of as an AI readiness checklist.
The items on the checklist include:
- The problem: The first step is to clearly define the business problem that needs to be answered and the goals to be achieved. This will ensure all decisions then follow a designated path.
- The data: It’s also important to have a clear understanding of what data is available and where and how it can be accessed. There is no point undertaking a project if required data is simply not available.
- The tools: Complete a thorough assessment of your organisation’s existing infrastructure and any tools that may already be in place. This may reduce costs and speed deployment.
- The skills: Next, take time to understand your current internal skillsets and identify any gaps. Expert assistance may need to be brought in to ensure the project’s success.
- The vendors: There are a variety of AI vendors with offerings on the market. Evaluate each to determine their power, usability, and ease of implementation given your problem, data and internal skillsets.
- Start small: Begin with a small project as a proof of concept, and carefully evaluate the achieved results before continuing.
- Evolve your approach: AI tools are constantly developing, so regularly review the approach you are taking to determine whether it is still the best way forward.
The momentum behind AI is building at a breakneck pace, and this will continue as usage and investment continues to rise in the future.
By taking the time to assess how AI’s capabilities can be best put to work within your organisation, you’ll be best placed to enjoy the benefits it can deliver.
