AI and Digital Transformation

What is artificial intelligence in a business context?

Artificial intelligence (AI) refers to all technologies capable of imitating certain human abilities (understanding, analysing, learning, predicting or generating content) in order to automate or improve tasks usually carried out by people.

In a business context, AI is mainly used to process large amounts of data more quickly, simplify internal processes and help teams make better decisions.

The difference between AI and automation

Traditional automation is based on fixed rules such as "if this, then that". It allows repetitive tasks to be carried out reliably, but without any real intelligence.

AI, on the other hand, goes much further. It detects trends, adapts to variations, learns over time and is capable of making more nuanced decisions depending on the context.

Direct link with digital transformation

AI is now becoming a fully-fledged accelerator of digital transformation. It enables organisations to move from :

• from a manual logic, where employees manage each step of a process,

• to an augmented logic, where tools support, automate and enrich human work.

The main categories of AI useful to businesses

Generative AI

It produces text, images, summaries or ideas from existing data.

Examples: automated writing, report generation, intelligent assistants.

Analytical (predictive) AI

It analyses large volumes of data to identify trends and predict the future.

Examples: financial forecasting, anomaly detection, sales analysis.

Conversational AI

It enables natural language exchanges via chatbots, virtual agents or internal assistants.

Examples: automated customer support, internal HR or IT FAQs.

Embedded AI in tools

Integrated directly into everyday software: ERP, CRM, Microsoft 365, accounting, sales tools.

Examples: recommendations, automatic classification, intelligent data extraction.

The benefits of integrating AI into companies

Artificial intelligence is transforming the way businesses manage their operations, analyse their data and interact with their customers.

For Quebec organisations, it represents an immediate lever for improving efficiency, reducing costs and making better decisions.

Automate repetitive tasks and cut costs

AI makes it possible to automate a multitude of manual processes that consume time and mobilise teams unnecessarily.

For example:

• Automated supplier invoice processing;

• Intelligent data extraction from PDFs, emails or forms;

• Automated classification of internal emails and requests.

Improving decision-making through advanced analytics

Thanks to predictive analysis, AI makes it possible to anticipate trends and take more informed decisions.

Examples of uses:

• Financial or budget forecasts;

• Detection of accounting or operational anomalies;

• Real-time performance analysis.

For managers, this means a better vision of the future and decisions based on reliable data.

Optimising the customer experience

AI helps deliver a faster, more personalised and more consistent service.

Common applications:

• Intelligent bots to respond 24/7 to simple requests;

• Analysis of customer sentiment from emails or forms;

• Automated segmentation of marketing audiences.

A better customer experience means greater satisfaction and a smoother service.

Enhancing safety and cyber security

AI also plays a role in protecting data and digital infrastructures.

It can :

• Detect incidents or suspicious behaviour in real time;

• Automatically apply security rules;

• Detect anomalies in access, transactions or data flows.

It is a lever for meeting the requirements of Law 25 and reducing internal and external risks.

Free up time for value-added tasks

By automating repetitive and analytical work, AI allows employees to focus on what really matters:

• Customer relations;

• Strategic analysis;

• Innovation;

• Planning and coordination.

This reallocation of time is one of the most appreciated benefits in a context of labour shortages.

How AI is transforming internal processes: concrete examples

Artificial intelligence is redefining the way organisations work on a daily basis. By integrating with the tools already in use (ERP, CRM, Microsoft 365, accounting software), it optimises all internal processes and creates new opportunities for efficiency.

Accounting and finance

AI makes it possible to eliminate a large number of manual and repetitive tasks:

• Automated invoice processing (OCR + classification);

• Intelligent banking approaches;

• Detection of accounting anomalies;

• Financial forecasts based on predictive models.

Human resources

In HR, AI supports both recruitment and internal management:

• Automated sorting of applications according to defined criteria;

• Analysis of data to anticipate workforce requirements;

• Internal assistants to answer employee queries (payroll, holidays, internal policies).

Operations and logistics

AI optimises supply chains and day-to-day operations:

• Sales forecasting to improve inventory management;

• Early detection of equipment at risk of breakage;

• Optimisation of routes or resources based on demand.

Marketing and sales

AI boosts sales performance by rapidly analysing large quantities of data:

• Automatic audience segmentation;

• Intelligent prospect scoring;

• Personalised recommendations;

• Customer behaviour analysis.

AI and human issues: collaboration, skills and adoption

The integration of artificial intelligence is transforming both technologies and ways of working. To achieve a sustainable digital transformation, organisations need to put people at the heart of the process.

Training and digital skills

AI requires new skills: using intelligent tools, interpreting data, managing automation and understanding risks.

Without training, adoption stagnates and benefits remain limited.

A new human/machine relationship

With AI, work doesn't disappear: it changes. The human being retains the final decision, while AI suggests, analyses, alerts and automates.

This co-piloting model allows employees to focus on strategy, creativity and customer relations, while the AI takes care of repetitive operations or complex analyses.

Change management and internal acceptance

One of the main obstacles is not technological, but human.

For AI to be adopted, we need :

• Reassure teams;

• Explain the benefits;

• Involve users from the outset;

• Support the transition with training and demonstrations;

• Adapt work processes.

Good change management reduces resistance, lessens anxiety and ensures smoother adoption.

The role of senior management: vision, culture and governance

Implementing AI requires clear leadership. Leaders must:

• Defining a digital vision aligned with business objectives.

• Instablish a culture where innovation is encouraged.

• Implement governance framing the use of data and AI (security, ethics, Law 25).

• Support teams in experimentation and learning.

When leaders are involved, adoption is faster, projects are better structured and risks are better controlled.

How can AI be integrated into your organisation?

Adopting artificial intelligence does not require a radical transformation overnight. Successful implementation depends on a gradual, structured approach tailored to your organisation's reality.

Step 1 - Diagnose your digital maturity

Before integrating AI, you need to assess where your organisation stands. This diagnosis will enable you to define a realistic plan, identify gaps and prioritise investments. This is the foundation for sustainable adoption.

Step 2 - Identify high-impact processes

Not all processes are good candidates for AI. The most profitable are generally those involving repetitive tasks, high volumes (invoices, emails, internal requests), critical processes such as sales or finance, or friction points such as deadlines or errors.

The aim is to quickly identify areas where AI can create tangible benefits.

Stage 3 - Defining priority use cases

Once your needs have been identified, you need to select a few realistic and measurable projects, such as automating invoice processing, automatically generating financial reports, forecasting sales or cash flow, or setting up an internal or citizen chatbot.

Each use case must meet a clear business objective: reduce costs, speed up a process, improve the user experience or enhance security.

Stage 4 - Prototype (PoC) and test

Before full deployment, a Proof of Concept (PoC) enables the solution to be tested in real-life conditions.

This prototype is used to check technical feasibility, measure potential gains, validate team buy-in and adjust the model according to actual needs. This approach minimises risk and facilitates decision-making.

Stage 5 - Implementation, training and optimisation

Once the project has been approved, the solution is deployed in the production environment. Teams are trained to use it effectively, while governance and security mechanisms are put in place to oversee the use of AI.

The models then need to be continuously monitored and optimised, because AI evolves with the organisation, its data and its objectives.

AI and digital transformation: which tools should you use?

To take full advantage of artificial intelligence, you need to rely on tools that are adapted to the reality of your organisation.

Power Platform: a complete suite

Microsoft's Power Platform is today one of the most accessible engines for integrating AI progressively and securely into Quebec organisations.

Power Automate

Power Automate automates workflows: document processing, internal request management, data synchronisation and automated notifications.

Power Apps

Power Apps lets you quickly create custom applications (HR, finance, operations) incorporating AI functions, without having to develop any code.

Power BI

Power BI transforms your data into visual dashboards, incorporating predictive analytics and AI-based recommendations.

Native AI solutions

Most of the major platforms now incorporate artificial intelligence directly:

Microsoft Copilot

Present in M365, it helps employees to write, analyse, summarise, prepare reports or automate daily tasks.

Azure AI

Advanced tools for analysis, computer vision, OCR, natural language processing and custom template creation.

Google Vertex AI

Powerful platform for generative AI, document analysis and prediction projects.

Turn AI into a concrete lever for your organisation

Artificial intelligence is more prevalent than ever, and has become a strategic tool that enables organisations to become more efficient, accurate and agile. Whether it's to automate your processes, improve your decision-making or support your teams on a day-to-day basis, AI can transform the way you work, simply and progressively.

At Mallette, our business advisors will support you from maturity diagnosis to the concrete implementation of AI solutions.

Do you want to integrate AI into your company and get tangible results? Let's talk about it today.