AI implementation in the office space depends on a robust framework that supports seamless working conditions. For instance, any AI-led framework would require a machine learning infrastructure, which would, in turn, need prerequisites like reliable data labelling and data pipeline. Moreover, a continuous quality analysis must be in place to ensure consistency in the data being used for the machine learning process. Therefore, before implementing and integrating AI into the day-to-day processes of a typical workday, employers must take good care of certain things.
Furthermore, AI implementation might look like a bit of experimentation at the beginning, and trusting its results must come at a gradual pace. The early performance of the AI system might not be entirely flawless, which is why the machine learning process must be taken care of responsibly. Special care must be taken to eradicate biases and build a system that can be counted on. In this article, let us look at the steps that must not be overlooked if implementing AI solutions in the workplace is in the pipeline.
Steps to follow in the AI implementation process
For a successful integration of AI into the workplace, the following must be ensured.
- Data literacy and data fluency: Data literacy refers to the basic understanding of how data works so that a working knowledge can be nurtured regarding the meaningful use of data. Data fluency, however, needs to be built like muscle memory, and thus incorporation of the same within daily conversations of employees is important. It must be recognised that the AI implementation process will be an enduring one, thus underscoring the need to have a sound understanding of the maturation phase of AI usage.
- Defining the drivers: To have an optimum AI usage, a suitable ecosystem must be facilitated. Constant market research must be conducted to understand how data is being harnessed outside the scope of the concerned business. Doing this will ensure a better understanding of data and pave the way for external data monetisation.
- Identifying scope: This point is perhaps the most important of all because it reflects the foresight and vision of an organisation. The best way to keep an enterprise one step ahead is to invest in areas of high variability and leverage on the resultantly high payoffs.
- Evaluation of in-house resources: Once the future scope of the business is understood, it is important to gauge the current firepower. Thus, it is imperative to align the latter with the former for best results. Moreover, the current workforce needs to be trained with the latest skillset so that there is no knowledge gap and seamless functioning of daily processes can be ensured.
- Employee support: There must be a system in place that directly addresses employee concerns regarding AI usage in their daily assignments. Additionally, the management systems need to be restructured to accommodate rising employee demands and support AI adaptability. Furthermore, team leads and other stakeholders must be incentivised for their participation and commitment to the company requirements regarding implementation of new technology in their operations.
- Selecting the right vendors: Working with a competent pool of vendors is an added advantage towards reinforcing revenues. In this regard, the ideal vendors would be the ones who have operations that are already aligned with the existing AI infrastructure, or are willing to adapt. Moreover, once the selected pool is decided, the company must revise service level agreements with them, keeping the changed operational scenario in mind to avoid any possible misunderstanding.
- Identifying and training candidates: Once the ideal candidates are selected based on merit and adaptability, they must be trained and made to prove their mettle. A sure shot way of doing so is to engage them in pilot projects to understand their current level of AI proficiency.Doing this would also help identify the right candidate who could potentially champion a live project according to their area of expertise.
- Measuring ROI: One way to immediately understand the efficacy of AI solutions is to look at the ROI it brings in, although a hasty judgement based on a single factor is not recommended. Still, if something is working well, there might be a good reason for it, and it must be leveraged to the business’s advantage. For instance, in case an AI model deployed by an NBFC works wonders towards new customer generation and retention of existing customers, care must be taken to optimise its functionality regularly.
To sum up
With the online marketplace becoming exceedingly competitive, companies cannot risk opting out of the fundamental changes brought on by AI. Whether it is through revolutionary changes to market research or a new approach in customer engagement, the fittest companies need AI to survive in the market. Therefore, implementing AI solutions in their workplace is only the beginning of realising their vision for the future. Finally, businesses should foster a healthy learning environment for employees so that they can contribute meaningfully towards realising the company targets.