What is generative artificial intelligence, and how can it revolutionize resource management, sales, and customer relations?
By integrating generative AI into our software solutions, Divalto helps you turn every interaction and every decision into a growth opportunity.
Discover how this innovation can transform your business management by streamlining operations and giving you a competitive edge.
As part of our ongoing innovation strategy to meet evolving user needs, we are enhancing our solutions by integrating generative AI to deliver even greater performance.
This new step forward aims to enrich the user experience across our platforms through the power of AI.
In this article, we present the first three generative AI features that will soon be available across our entire product line.
Artificial intelligence is the fastest-evolving digital technology in recent years. Its many benefits are well established: easier access to information, automation of repetitive and time-consuming tasks, enhanced operational efficiency, and more.
AI also empowers better decision-making by quickly analyzing large volumes of data — providing valuable insights that support business strategy.
With the launch of new generative AI functionalities based on Microsoft Azure OpenAI Service, which gives access to powerful models such as GPT and o1, we are continuing our approach of constant innovation. The aim of this investment is to add natural language text understanding and generation capabilities. These new features will enable users of our Divalto business, Divalto field service, Divalto industry and Divalto weavy solutions to save time on low value-added tasks, by manipulating and/or exploiting business data more rapidly.
Among the most common uses of artificial intelligence, generative AI is the most accessible to the general public and the most massively developed for professionals’ everyday needs. With the help of a few words (prompts), it can generate, reformulate or modify text according to the user’s wishes.
This new tool will soon be available in all our products’ “long text” and “rich text” fields, and will benefit from further developments to further enhance its performance.
Examples of use cases :
Objective: automate text creation and manipulation to improve user productivity and accuracy.
This artificial intelligence functionality will be integrated into the next ERP SaaS and CRM versions, due for release in November 2024.
Initially, it will be made available as a Beta version to partners, before being offered to all users of the Divalto one platform during 2025.
We will also be offering the possibility of creating business prompts specific to certain functional modules, according to user needs: summarizing a business opportunity, indicating the progress of a deal and potentially blocking elements, generating a message to send a quote, proposing a message for a contact, etc. The aim is to capture use cases as close as possible to the user and implement them rapidly.
The aim is to capture use cases as close as possible to the user, and rapidly implement them. This personalization capability will be available in 2025 by simple no-code parameterization for business prompts and via a new development kit to enrich the contexts known by AI.
We are also working on a “Chat”- or “Copilot”-style assistant to access all our ERP and CRM solutions in natural language. A true right arm for users, this tool will offer a wide range of actions, taking into account the context of use, in order to respond to users’ requests and, ultimately, to suggest tasks to be carried out and launch the corresponding actions (create a quote, record a reminder, reschedule a maintenance intervention, trigger a replenishment order, etc.).
Its function will be to understand and respond to user requests expressed in the form of a natural language conversation, and to act as a genuine productivity assistant.
“Our priority is to integrate AI functionalities that are thought out and made for business users. We therefore place a very strong emphasis on the personalization of this artificial intelligence in order to offer relevant and genuinely useful functions.” Christian Dhinaut.
This innovation will be integrated into the solutions and all ERP and CRM users of the Divalto one platform by the end of 2025. Also worth noting: we’re also working on AI assistants for developers in our partner network.
“By integrating AI, companies can reap tangible benefits with measurable ROI. Thanks to its ability to automate certain tasks and streamline operations, they gain in efficiency and productivity. According to a recent study on the productivity of generative AI , 45% of executives estimate that their employees’ productivity has doubled thanks to GenAI alone. Today, we’re going one step further: we’re putting AI at the heart of small and medium-sized businesses’ information systems. The use cases we propose are directly linked to the needs expressed in the field by our users. So, in addition to generative AI to help generate and rework textual elements, we are developing business-specific prompts for our business solutions dedicated to industry, maintenance and so on. We offer, among other things, the possibility of summarizing a business opportunity, indicating the progress of a deal or identifying obstacles. The Copilot-type assistant we’re working on will enable us to create a quotation, or trigger a replenishment order – recurring needs within the businesses we address. At the same time, thanks to their expertise in our solutions and their knowledge of our customers, our partners will be able to develop new use cases on their own.” Jérémy Grégoire, Chief Executive Officer.
1
Generative AI plays a crucial role in the evolution of CRM and ERP systems, enabling the optimization of customer relationship management through advanced machine learning algorithms and artificial neural networks.
Companies that integrate AI-powered CRM and/or ERP systems benefit from multiple advantages, including the automation of repetitive tasks, enhanced customer experience, and increased personalization of interactions.
By leveraging predictive algorithms, AI-powered ERP and CRM solutions can analyze large volumes of data to anticipate future customer needs and behaviors.
This enables marketing and sales teams to deliver personalized recommendations and optimize loyalty strategies. For instance, an AI-enhanced ERP or CRM can process real-time data from past interactions to tailor offers to each individual client — improving both conversion rates and customer satisfaction.
AI-driven CRMs also allow for more efficient customer service management, particularly through the automation of responses to frequently asked questions via intelligent chatbots. These systems use deep learning and voice recognition to interact seamlessly with users while reducing the workload on human support teams.
Artificial intelligence applied to CRM also provides forecasting and planning capabilities, using data mining techniques to uncover hidden trends in customer data. This helps companies better anticipate purchasing behavior and adapt their strategies accordingly, making their processes more agile and personalized.
For businesses looking to stand out, integrating AI into their ERP or CRM systems is a key driver of digital transformation.
It enables them to become more agile, proactive, and data-driven. By combining automation, prediction, and personalization, these solutions are becoming essential tools for improving customer relationship management.
Optimizing your CRM and ERP systems with artificial intelligence results in greater operational efficiency while boosting customer engagement and satisfaction.
2
Generative AI and CRM Automation: A Game-Changer in Task Management
CRM automation has become a key priority for companies looking to streamline processes and boost efficiency. In this context, generative AI is emerging as a breakthrough technology, capable of automating repetitive tasks within customer relationship management systems. But how exactly is generative AI contributing to this transformation?
One of the main advantages of generative AI in CRM automation is its ability to handle repetitive tasks that would otherwise consume hours of manual work. For instance, data entry, updating customer information, and generating reports can all be automated using intelligent algorithms. This frees up time for sales and marketing teams, allowing them to focus on higher-value tasks such as strategy development and customer relationship building.
By integrating generative AI into a CRM system, companies can also enhance their operational efficiency. AI-powered CRM automation tools can analyze customer behavior and predict their needs. For example, AI can detect patterns in purchasing data and suggest targeted marketing campaigns. This higher level of personalization can increase conversion rates and strengthen customer loyalty.
Another key benefit of CRM automation through generative AI is the reduction of human error. Manual tasks like data entry are prone to mistakes, which can be costly for the company. Automating these processes leads to more accurate results and supports better decision-making. As a result, teams can rely on clean, consistent data without concerns over inconsistencies.
Generative AI not only improves internal efficiency — it also transforms the customer experience. With AI-powered chatbots, companies can respond instantly to customer inquiries 24/7. These CRM automation tools deliver relevant, real-time information, boosting customer satisfaction and reinforcing brand loyalty.
A common concern for businesses exploring automation is how new technologies will integrate with their existing systems. Fortunately, many CRM automation solutions are designed to work seamlessly with ERP platforms and other business tools. This allows companies to leverage generative AI without having to rebuild their tech stack from the ground up.
3
Generative AI has transformed data management across numerous industries, offering opportunities for optimization and improved efficiency. However, its adoption also comes with certain risks. Below are key challenges and concerns linked to its use.
One of the primary risks lies in the quality of the data used to train AI models. If the input data is biased or incomplete, generative AI will produce equally biased or inaccurate outputs. This can lead to decisions based on flawed information, ultimately compromising the reliability of analyses and recommendations.
The use of generative AI in data management raises significant concerns around security and data privacy. AI systems often require access to large volumes of data, including sensitive or confidential information. Poor handling of this data may result in privacy breaches or information leaks. Organizations must implement robust safeguards to protect against cyber threats and ensure compliance with data protection regulations such as Québec’s Law 25.
Generative AI can also be used to create misleading or false data, such as deepfakes or fabricated content. This poses significant risks, particularly in marketing and communications. Companies may unintentionally distribute false information, potentially damaging their reputation and eroding customer trust.
Another concern is the increasing reliance on generative AI tools. Over time, this dependency may lead to a decline in human data management skills and a loss of control over critical decision-making processes. If employees rely too heavily on AI outputs without critical evaluation, it can result in major operational errors.
Lastly, ethics and transparency remain major challenges. Generative AI algorithms are often seen as “black boxes,” making it difficult to understand how decisions are made. This lack of clarity can raise accountability issues, especially when errors or harm arise from automated decisions. Companies must prioritize transparency and traceability within their AI-driven processes to build trust and ensure responsible usage.
4
Before measuring the ROI of generative AI, it is essential to define specific and measurable goals. For example:
– Are you aiming to boost sales efficiency?
– Reduce operational costs?
– Improve customer satisfaction?
These goals must be realistic and aligned with your company’s strategic priorities.
Take into account all costs related to the integration of generative AI, including:
Use this formula to calculate the return on investment:
ROI = (Net Benefit / Investment Cost) × 100
Where Net Benefit equals the gains from generative AI minus the implementation costs.
A positive ROI indicates a profitable investment.
Ongoing performance monitoring is crucial. Assess outcomes over defined periods (e.g., quarterly or annually) and adjust your strategy accordingly. This ensures that your generative AI initiatives remain aligned with business goals and continue to deliver value over time.
