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You Want AI. Now, How Do You Start?

You Want AI

The impact of AI can be felt in pop culture as well as our daily lives. AI has been making headlines with its ability to compose music, make artworks, and create movie trailers. Looking at the potential of AI, multiple businesses are using AI to generate analytics, increase workplace productivity, prevent fraud, and streamline various business procedures. If you wish to adopt AI for your business, you need to develop a comprehensive adoption strategy. An effective strategy can help you plan for infrastructure, software development, budget, and implementation. In your strategy, you can consider the following steps.

Define Use Cases

To implement AI effectively, you need to identify priorities and goals for your business. These goals can be developing better products, improving productivity, enhancing customer experience, and many more. After identifying your business goals, you need to understand how AI can help you achieve these goals. To summarize, you need to ask yourself the following questions:

  • What are my business goals?
  • Which issues need to be addressed as soon as possible?
  • How AI can help my organization achieve its business goals?

You need to analyze how the output generated with the help of AI will affect your business. Based on such analysis, you can identify AI use cases that would benefit your business. Identifying suitable use cases will help you decide your software development approach for adoption and implementation of AI.

Identify Data Sources

Collecting and analyzing crucial data is a necessity for AI systems. Hence, you have to identify which types of data will be required for implementing AI use cases effectively. Such data can be historical as well as real-time. Crucial data can be collected from various sources such as social media, personal information of customers, and public datasets. Recognize which type of data is offered by various data sources and which types of data will be beneficial for your business. After identifying suitable data sources, you can start collecting data from the selected sources and optimize it for AI systems.

Prepare for Data Storage

Before implementing AI in your business, you need to develop an effective data storage strategy. AI will require an increasing volume of critical data that is aggregated constantly. AI systems become more accurate and reliable with increasing amounts of data. In case you fail to plan for data storage, you might face several obstacles while implementing AI.

To store data for AI systems, you need to consider using multiple data centers that include multi-core CPUs and GPUs. These systems must use parallel processing along with high-speed networks to avoid I/O bottlenecks in data processing and transfer. You can also utilize cloud services for data storage.
Allocate sufficient budget

To adopt AI effectively, you need to allocate a sufficient budget for your AI project. In your budget, you should plan for infrastructure as well as the employees. While creating your budget, evaluate the estimated ROI of your AI project. In case you face a shortage of funds, you can collect private investments for your project.

Hire Skilled Professionals

While creating an effective adoption strategy, you should collaborate with professionals who are experienced in dealing with AI. Such professionals will inform you about various technicalities of AI adoption and implementation that you may not be aware of. Hence, you need to hire a dedicated team of skilled professionals. These professionals can handle various intricacies involved in the implementation of AI and software development, helping you become prepared for risks that might be involved. Experienced professionals can also help you identify possible errors in your strategy and future risks in your approach. Therefore, hiring a dedicated team of consultants, programmers, and software development experts is a necessity. Also, you need to educate your existing employees about the benefits and utilization of AI.

Integrate with Enterprise Systems

Using AI and enterprise systems separately may result in the generation of data silos. To avoid this issue, integration of AI with existing enterprise systems is necessary. By integrating with enterprise systems, you can utilize AI to its maximum potential and use different data sets together. With this approach, you can identify different patterns in available data and find inconsistencies that need to be resolved. With integration, you can also use AI to improve workplace productivity and employee performance. For instance, utilizing AI for tracking employee attendance and performance can offer you insights into every employee’s performance with the help of detailed monthly reports.

Plan for Data Security

Since AI collects large volumes of sensitive data, you must plan for data security. For starters, you must encrypt all the collected data. Using encryption, you can ensure the integrity of your data. In case any hacker gains illegal access, encryption can protect your data from being viewed or altered. Additionally, implement restricted access to ensure that any unauthorized person cannot get access to confidential data. Along with encryption and restricted access, you need to ensure that your networks are secure. For this purpose, you can use an intrusion prevention system that proactively scans your network traffic to identify suspicious activity.

Research has shown that over 40% reported security breaches are caused due to employee negligence. Hence, you need to educate your employees about various cybersecurity threats and ways to protect themselves as well as the organization from cyber attacks.

These steps will help you develop an effective adoption strategy and get started with AI. However, there are several risks and intricacies involved in software development, integration with enterprise systems, and overall implementation that may go unnoticed during the planning stage. Therefore, outsourcing AI-based development can be the most feasible approach for you. Reach out to Digital Fractal for AI-powered software development and mobile app development.

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