Generative Artificial Intelligence presents great opportunities for companies. We explore the steps to be followed for successful implementation.
Generative AI in the enterprise: promising opportunities and challenges to overcome
Generative AI (Artificial Intelligence) is rapidly emerging as one of the most revolutionary technologies in the modern business landscape. Thanks to its ability to create original content, optimise processes and improve operational efficiency, many companies are looking to integrate this technology into their business models. However, its implementation is not without its challenges.
Although Gen AI offers exciting new opportunities for companies, currently only 30% of Italian companies have already adopted it, while a further 30% expect to do so within the next year and 31% within two years. These are the findings of a survey conducted by Coleman Parkes Research on behalf of Sas.
The adoption of Generative AI in companies is hampered by several critical factors. One of the main ones is the lack of adequate tools needed to implement these technologies effectively. Organisations often face uncertainties regarding the use of data, both internal and external. A further obstacle is the complexity of the transition from theory to practice. In addition, companies struggle to demonstrate a return on investment. Integration with existing business systems is also a significant challenge. Finally, another limiting factor is the lack of in-house expertise.
Generative AI: opportunity or risk?
The survey results show that, despite much talk about Generative Artificial Intelligence and despite the enthusiasm of many, there are still many companies that view this innovation with scepticism.
Goldman Sachs, a leading company in investment banking and in the management of shares and derivative instruments, in its report ‘Gen AI: Too Much Spend, Too Little Benefit?’, casts doubts on the economic return of the huge investments that technology giants, and others, are making and will make in the coming years in Generative AI.
Despite the doubts and uncertainties surrounding its adoption, it is possible to effectively and profitably integrate this technology into companies, provided that impulsive choices are avoided and a strategic and well-considered approach is adopted.
The 5 steps to correctly implement Generative AI
To make the most of the benefits offered by Generative AI innovation, companies must follow five essential steps. Let’s see what they are.
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Assessing your needs
Generative Artificial Intelligence is a valuable resource in many areas, yet the needs of companies can vary significantly. Therefore, the first fundamental step is to fully understand the specific needs of each company. This implies an in-depth analysis of the processes currently in place, in order to identify areas where Generative AI could add substantial value. For example, in marketing companies, Generative AI can be harnessed for the creation of tailored advertising content, while in manufacturing companies it can help improve and optimise product design.
At this stage, it is crucial to set clear and measurable goals, in order to have a precise benchmark on which to base future evaluations regarding the effectiveness of the implementation of Generative Artificial Intelligence. Furthermore, it is essential to define precise evaluation metrics, such as return on investment (ROI), reduction of production time and optimisation of the quality of generated content. -
Choosing a Generative AI platform
Once you have identified your company’s specific needs and understood how Generative Artificial Intelligence can be profitably applied in your business context, you can start analysing the various Generative AI solutions available on the market.
The options are numerous, and each has a unique set of features and functionality. It is crucial not only to examine the inherent capabilities of each product, but also to consider the type of technical support that is provided, the costs associated with implementation and maintenance, and the level of reliability and security that each system can provide. This evaluation process is crucial to making an informed choice that meets the company’s specific needs.
It is essential for companies to also explore the limitations of these technologies so that there are no false expectations about what they can really offer. A clear understanding of the capabilities and constraints of each application will allow them to avoid investments that may prove inadequate or unprofitable.
In addition, it is important to consider the scalability of Generative AI platforms, their security, ease of use, and ability to integrate with one’s own infrastructure. -
Developing a data management strategy
Generative Artificial Intelligence requires a constant supply of data, which must possess high quality standards to generate meaningful and reliable results. This technology is characterised by its ability to create valuable outputs, especially when using cross-sectional data. For example, when combining production data with data from in-depth market analysis, Generative AI can offer useful suggestions on how to optimise an existing product or how to develop a new one.
The importance of having access to well-structured, organised and easily available data that is always up-to-date cannot be underestimated. -
Integrating Generative AI with business processes
Integrating Generative Artificial Intelligence into existing business processes is the next step. This process cannot take place without a careful assessment of the level of staff readiness and the impact the adoption of this new technology will have on people and workflows.
To begin with, it is essential to recognise that the successful implementation of Generative AI requires adequate employee training. Those who will be involved in using this technology must have a clear understanding of both its potential and its limitations. Only through proper training can employees learn how to make the most of Artificial Intelligence and apply it profitably in their daily activities.
Furthermore, it is crucial that employees not only understand the technical capabilities of Generative AI, but also take on board the ethical implications and responsibilities associated with its use.
Fostering a corporate culture that is open to innovation and experimentation is key to fostering an environment where employees feel supported in learning and adopting new technologies.
To assess the impact of Generative AI on the organisation, existing workflows need to be reviewed and clearly defined. This review may involve changes to operational processes in order to integrate AI optimally. It is also important to establish who will be responsible for the use of AI, so that business objectives can be achieved effectively and in accordance with industry best practices.
A useful approach to begin the implementation of generative AI is to start small-scale pilot projects. These projects allow artificial intelligence to be tested in a controlled environment, allowing the company to experiment without exposing itself excessively to the risks and costs of a large-scale implementation. In addition, conducting small-scale tests allows any technical or integration issues to be identified and resolved more effectively, thus facilitating the transition to more ambitious projects. -
Monitoring results
After the initial implementation of Generative Artificial Intelligence technology, it is crucial to start an ongoing monitoring process to assess its efficiency and impact on various business processes. This monitoring serves to identify any areas that could benefit from improvement. Indeed, a new technology does not always immediately bring the expected results. Therefore, it is important to keep an eye on performance in order to understand how to optimise the use of Generative AI.
A crucial part of this process is the feedback that needs to be collected from staff and end users. This feedback is valuable as it provides direct insight into how the new technology affects day-to-day activities. Operators and users interacting with Generative AI can provide useful information on any difficulties encountered, desired improvements or features that are particularly useful. Gathering these opinions not only helps evaluate the effectiveness of the technology, but also allows it to be better adapted to specific operational needs.
Monitoring should not be seen as an isolated activity, but rather as a continuous and dynamic process. Business needs may evolve over time due to various factors, such as changes in the market, new business strategies or the emergence of new technologies. Consequently, it is important that the use of Generative AI adapts to these changes, ensuring that it always remains aligned with the company’s goals and needs.
