7 Challenges of Adopting Artificial Intelligence in Businesses

Artificial Intelligence (AI) is the new buzzword in the commercial sector. All the tech giants are leveraging the technology to bring out products...

  • 7 Challenges of Adopting Artificial Intelligence in Businesses
    Liam Walker Image Liam Walker

    7 Challenges of Adopting Artificial Intelligence in Businesses

    • Updated: Monday 26th of October 2020
    • Strategy

    Artificial Intelligence (AI) is the new buzzword in the commercial sector. All the tech giants are leveraging the technology to bring out products that have been revolutionising our lives. Several big and small enterprises are adopting AI and machine learning to streamline processes, improve analytical data collection, enhance customer satisfaction and make predictions with accuracy. It has helped companies to automate various time-consuming and tedious procedures and intensify their productivity.

    However, the percentage of businesses utilising the technology is still relatively small as they are faced with implementation challenges. If you are planning to purchase a business for sale in Australia, then you should make sure that you are aware of these upheavals to tackle them skillfully. So here is a list of the most common troubles that affect businesses while adopting AI.

    1. Lack of Expertise

    Most organisations do not have employees who specialise in AI and machine learning which limits their capitalisation ability. They need experts from the field along with subject matter experts who can help to move the project in the right direction. These individuals should be aware of the technical issues which can crop up during the implementation and should be ready with solutions. Since it is a relatively new technology, it becomes difficult to find qualified and experienced people in the field. The team working on the deployment must ensure to align the process with the long-term goals of the organisation to make it a success.

    Thus you must find data scientists and train people in AI-based work to allow seamless integration of the technology. You can focus on training the existing workforce if you are unable to find the right talent.

    2. Quality of Input

    AI and machine learning are dependent on massive streams of data that needs to be fed into the systems continuously. Thus you must have a vast quantity of high-quality data which gets utilised by the machines. The output is only as good as the input. Therefore, you need to find relevant and valuable information and label it correctly to allow the machines to interpret it effortlessly. Shortage of data I yet another challenge that can hold back the effective functioning of the process.

    Also, AI analyses data at a much faster rate than humans, so you need to prepare a strategy for quick computation too. You must identify the existing amount of data and the amount that is required for achieving the desired results. You can conduct surveys or utilise your market research to create new sources of information. In addition, you can purchase data from research companies or outsource the work to a third party. You can also analyse the data available online and screen it for relevant information.

    3. Undersupplied Infrastructure

    Most organisations face the challenge of having an unsuitable infrastructure for deploying AI applications. To leverage AI for your business, you need a lot of groundwork, such as making arrangements for data collection, storage, privacy, labelling, interpretation and scalability. The technology can be successfully adopted only when the business is ready with an efficient set-up. The basic requirements for the foundation of AI include high-speed computation system, software and hardware that is apt for the applications, cloud storage, and scalable systems that work with the AI applications.

    As the owner, you will have to create new processes and workflows that match the requirements of AI solutions.

    4. Protection of Data

    Since the AI applications have to interpret and analyse massive amounts of data, the storage of this gigantic business information becomes a challenge. The threat of data breaches also looms large because of the increasing identity theft cases across the globe. The data being fed into the applications is often classified information which needs to be kept safe. Privacy of customer information is highly crucial, and this is the reason why the European Union has come out with the General Data Protection Regulation (GDPR).

    However, Australia has only provided a framework for self-regulation. Thus entrepreneurs have to be on their toes to ensure that they comply with the guidelines at all times.

    5. Budget Allocation

    The cost of adopting AI is on the higher side. As stated above, you will have to hire experts or train people, create new policies, and set up an entire infrastructure suitable for the implementation of AI applications. All of these tasks involve huge costs, and you must have a budget planned for this purpose.If you fail to do so, then you may end up exhausting your valuable funds and affecting your bottom-line. If the company is struggling with finances, then it is not feasible to adopt AI. It must be implemented only when the organisation can spare sufficient funds for the project.

    6. Meeting Business Needs

    Before the integration of the technology, the business owner should be clear about the usability. You must determine which problems can be effectively solved with the help of AI applications and how they will benefit the business. You will have to develop a strategy to make the technology an integral part of the organisation and future endeavours to improve productivity. You must have defined goals for the project and align them with the business objectives to match the needs of the company.

    Also, AI does not provide results overnight. It is an ongoing process which can be embraced by a flexible structure. Instead of following the herd mentality, the business owner should be certain about the need for AI and what can be achieved with its help.

    7. Prejudiced Results

    One of the controversies doing the rounds is that the AI applications are offering biased results. For example, the systems appear to be prejudiced towards a section of the society. However, one needs to understand that AI does not have a mind of its own. It learns from the data provided to it. If the data fed into the system is biased, then the output will automatically become biased.

    For instance, if the data is collected from a group of men in their 50s, it cannot be generalised for the entire population. Some problems have emerged related to this issue with various companies. However, it can be effectively resolved by choosing the right data collection methods.

    Conclusion

    Adoption of AI requires a thorough understanding of the technology and identifying its suitability in your work environment. The next step is to develop an implementation strategy and going forward in a systematic manner. Thus if you are planning to purchase a business for sale in Australia, then make sure that you are aware of the challenges mentioned above to face them with competence.

  • Author Info Liam Walker

    Liam Walker has been a business expert for around 40 years and had specialisation in the franchise sector. He is passionate about helping people by guiding and motivating them to become financially secure and independent through business. His free training sessions on “How to Achieve, What you Desire” has changed many lives for good. Business2Sell  is honoured to have Liam as their Guest Author.