Today there are many, many AI technology solutions and hundreds of these providers promise you that they will solve your problems and that their technology solutions have everything you need to solve your need or that AI assistants are the salvation for all your pains. For example, research showed that by incorporating generative AI, a company with 5,000 agents resolved incidents 14% faster and reduced management time by 9%, highlighting the importance of planning and applying AI effectively to make a real impact.
All this may be a fact, but before you act and buy artificial intelligence, you should think: what kind of solution your main vendors are offering you. There are two strands here:
- Customizable or custom-built AI products to solve your pain points. This is an AI solution that is specific to a company and targeted to a specific problem. Since the custom AI solution is developed for a single company, it must meet the company's specifications and expectations.
- Out-of-the-box, 'Plug-and-Play' AI products, which are standardized off-the-shelf products with minimal configuration, a packaged solution sold by vendors to meet the needs of numerous organizations.
According to Gartner (one of the largest technology research and consulting firms), by 2027, more than 50% of Gen AI models used by enterprises will be specific to a business sector or function, compared to approximately 1% of Gen AI models used by enterprises in 2023. This leads us to think about the importance of planning the deployment of multiple Gen AI models. According to Gartner, enterprises should look for out-of-the-box domain-specific models that you can train or tune to fit your business needs.
Other platforms also mention that 'plug-and-play' solutions are the future of AI-enabled CX and so should be set up for all forms of customer service, at the same time, it is clear that developing custom AI software for your company from scratch comes with considerable costs and, above all, time. Training and calibration of AI modules are time-consuming tasks that require highly qualified specialists.
However, modern AI solutions require a certain degree of expertise, as they are data-driven. According to AIMultiple (one of the largest European companies offering comprehensive high-tech analysis), it takes considerable effort to obtain the data and build a high-performance model, and there are currently numerous areas where mature AI solutions do not exist.
When it comes to artificial intelligence, most rely on existing AI on the market, but in many cases, these offerings are not able to meet the specific needs of the business. This causes many companies to look for custom development, because they cannot find existing software that meets their needs and truly fits their requirements.
In this article we want to tell you and give you solutions (with real bases), what you should analyze when considering buying an AI technology solution because we want to help companies to discover the path to success with generative AI and to know when it is better to take each alternative. You need to be able to evaluate which of all the tools on the market today fits your real needs, the type of company you are, the type of corporate culture you have and even the reality of your employees. That is why this is a decision that you should analyze with caution... Let's begin.
Key points of Plug & Play Solutions
Benefits
- Quicker Deployment: Deployment time is shorter and less costly by reducing your product development time by integrating a commercial AI module.
- Lower Upfront Costs: This is ideal for companies with tighter budgets. You save the cost of integrating commercial solutions, including initial licensing fees, is usually lower than developing such a solution from scratch.
- Support included. AI solution providers usually offer support, i.e., they release updates with new functionality and bug fixes.
- Predefined architecture and data format. There is no need to design the architecture of the custom AI software or invent the format of the data needed to train the AI module, as the packaged software has fairly clear requirements for the input parameters.
Disadvantages
- Implementation constraints. Any integration may impose certain restrictions on your software and its architecture. That is, you may lose the flexibility and openness of the system. If, for some reason, the ready-made AI solution does not fully cover the functional and non-functional requirements, you will have to change the scope of the project to integrate the selected AI-based module.
- Increased licensing costs. With the increasing popularity of such products, the cost of licensing to use a third-party AI solution may increase. In addition, some vendors use a non-linear royalty calculation method, setting the price based on the revenue of the final product.
- Specific knowledge to set up a third-party AI solution. One disadvantage of low-code or no-code AI platforms is the need to learn how to configure this software, with no guarantee that your team will use this knowledge in future work. In addition, many out-of-the-box solutions have poor documentation, and vendors sometimes implement significant changes that result in the need to retrain the team.
Key points of Custom-made AI Solutions
Benefits
- Customization: Exact personalized to specific processes and needs.
- Support and Maintenance: There is a higher level of technical support and maintenance customization.
- Medium-term ROI: Although the initial cost is higher, the long-term savings in operating costs and increased efficiency justify it.
- Off-the-shelf solutions have limited performance: Custom AI solutions can achieve higher performance compared to an off-the-shelf solution.
- Configure an existing open source or closed source solution to better meet the needs of the organization: For example, most companies use ERP software from well-known vendors. However, given the diverse requirements of different companies, ERP systems need to be configured thoroughly. This configuration can take months, but it is crucial for effective use of the software.
- Some claim that there are no off-the-shelf solutions: AI is an emerging field and there are no mature solutions for all business functions or industries.
Disadvantages
- Implementation time: Exact adaptation to specific processes and needs can be a complex and time-consuming task. Developing a customized solution requires a thorough understanding of the company's needs and a detailed analysis of its processes. This customization involves the creation of specific algorithms and the integration of the company's own data, which can significantly increase cost and development time. In addition, any changes in business processes may require continuous adjustments and updates to the IA solution.
- High Support and Maintenance Costs: A customized IA solution requires a higher level of ongoing technical support and maintenance. This is because any problems or failures must be addressed by specialized technical personnel who understand the specifics of the implementation. Maintenance of the custom solution may include updating algorithms, adding new features, and resolving compatibility issues with other enterprise systems. This type of specialized support can be costly and difficult to manage without a robust and experienced technical team.
- IA Field Maturity: IA is an emerging field, and there are no mature solutions for all business functions or sectors. This means that companies may face difficulties in finding standardized solutions that perfectly fit their needs. In many cases, creating a custom solution may be the only viable option, but this comes with the challenges and costs associated with developing from scratch and uncertainty about the performance and effectiveness of the solution.
Use Cases and Real Situations
Cuándo Optar por una Solución Hecha a la Medida:
- Need for High Customization and Integration: If your company has complex and specific processes that require a high degree of customization and integration for communication with your customers, a custom AI solution may be more suitable.
For example: Customers often need to transfer the products/services they require from an old to a new address due to a relocation or other reasons. However, initiating this transfer can be a cumbersome and time-consuming process, involving multiple steps and interactions with customer service representatives, such as calls, questions and more questionnaires.
By Implementing an AI-powered virtual assistant accessible through multiple communication channels (such as website, mobile app or phone). The assistant allows customers to easily request and schedule service moves by providing the new company address and desired move date. Thanks to its natural language understanding capabilities, the wizard guides customers through the process, ensuring that all necessary information is accurately collected. By streamlining the relocation request process, the wizard reduces customer effort and improves their overall satisfaction with your company as the service/product provider.
- Financial Performance and Efficiency: Standard solutions can have limited performance. For applications with significant financial impact, such as improving sales efficiency, a custom solution can offer greater benefits compared to an off-the-shelf solution. For example: Customized conversational AI solution platforms can handle routine queries that customers ask when they call, freeing call center agents to focus on complex issues. This greatly reduces call volume and wait times, ensuring faster support and higher customer satisfaction.
- Configuration and Data Requirements: Standard solutions may require significant configuration and may not perform well if your company's data does not align with the model's training data. Providing more training data or working with consultants may be necessary to improve the performance of the standard model. For example: A customer has an urgent claim to make about a product or service after hours. By using an AI-based virtual assistant, available 24x7, the customer can discuss their complaint, as well as add additional information during the process without the need for human intervention, as the AI will understand the user's natural language.
When to Opt for a Plug & Play Solution:
- Fast and Economical: If you are looking for a fast and economical solution for general needs, plug-and-play models are ideal as they are pre-trained and configured for immediate implementation, which would not allow you to make modifications to established responses/functions.
- Implementation in Days: You need the solution to fit your company in a matter of days, which is possible with plug-and-play models that do not require long development and training periods.
- Low Investment Cost: With limited resources, a plug-and-play system offers economic advantages by saving on development costs and reducing time to market, allowing for a faster return on investment.
In the following table we show you an evaluation where you can analyze which option meets your needs:
Understanding what to consider when making a decision
Prior to choosing Plug-and-Play:
a. Before choosing a plug-and-play solution, companies should ask themselves whether they need a quick and cost-effective implementation, whether their processes are general enough to be covered by standard solutions, and whether they are willing to rely on the vendor for upgrades and support. They should also consider whether they have the in-house technical capability to configure and maintain the solution effectively.
b. Characteristics to consider when selecting a plug-and-play solution include a limited budget for upfront costs, an urgent need to implement the solution, standard and general business processes that do not require much customization, and a technology infrastructure that allows for quick and easy integration with existing systems.
Before choosing Custom AI Solution:
a. Before opting for a custom AI solution, companies should ask themselves whether their needs are specific and complex, whether they can bear a higher upfront cost for long-term benefits, and whether they have the technical and human resources to develop, implement and maintain a custom solution. They should also evaluate whether the customized solution can integrate with their current systems and processes efficiently.
b. Characteristics to have as a company to select a customized solution include having unique and complex business processes that require high customization, having an adequate budget to cover upfront costs and necessary resources, having a qualified technical team or the ability to hire specialists, and a flexible technology infrastructure that allows for the development and integration of a custom solution to maximize efficiency and long-term financial performance.
Conclusion
When deciding between implementing a plug-and-play or a custom artificial intelligence solution, it is crucial to carefully consider your needs and resources. Plug-and-play solutions are ideal if you are looking for a quick implementation and have a limited budget. These options allow you to integrate AI quickly with minimal configuration and without the need for a lot of technical resources, which is perfect if you need an immediate and effective solution without extensive development.
On the other hand, if your company has complex and specific processes, a customized AI solution may be more beneficial in the long run. Although they require a higher initial investment and more time to implement, these solutions offer flexibility and customization that can significantly optimize your operational efficiency and reduce costs in the long run. Opt for custom AI if you have the technical and human resources to develop and maintain it, and if you are looking for deep integration that is specifically personalized to your unique needs.
