Generative AI: Practical guide for business managers

Generative AI: what are we really talking about?

What is generative AI?

Generative AI is a technology capable of create new content based on your instructions in natural language. Where other AIs are analytical or predictive, generative AI, as its name suggests, generates: text, images, code, analyses.

It's a bit like an ultra-competent intern who can write, analyze, or summarize, but who needs guidance and whose work needs to be checked. Generative AI does indeed have its limits since it is likely to “hallucinate”, that is to say invent plausible but false information. This is why human validation remains absolutely essential.

Generative AI does not replace the human, it increases it by automating repetitive tasks to free up time on what really matters.

Generative AI in the Microsoft ecosystem

Microsoft has democratized access to generative AI by integrating it directly into the tools your teams already use, as part of its professional offerings:

• Microsoft Copilot is your AI assistant integrated into Word, Excel, Excel, PowerPoint, Outlook, and Teams.
• Copilot for Dynamics 365 integrate AI into your CRM to analyze customer interactions.
• Copilot Studio allows you to create custom AI agents without advanced technical skills.
• Azure OpenAI Service provides access to the most advanced models for complex use cases.

What sets Microsoft apart is that the security and compliance are native there. In the context of professional offers, your data remains private, is never used to train public models, and respects the GDPR.

Why focus on generative AI now?

According to the study ”The economic potential of generative AI“ published by McKinsey in June 2023, generative AI can improve the productivity of certain cognitive tasks by several dozen percent, depending on the use case. The Microsoft Work Trend Index (2023) indicates that Copilot users report save an average of around 29% of time on certain office tasks.

Technology is now mature and accessible. With Copilot, it integrates naturally into your existing workflows, and the return on investment is measured in weeks, not years. So the question is no longer whether you should start, but where to start.

Marketing and communication opportunities

Accelerating content production

Your marketing teams spend hours producing content while demand keeps growing. Generative AI is changing this state of affairs.

With Copilot, your marketing manager can generate 10 variants of a LinkedIn post in two minutes instead of one hour. It adapts content for different channels in seconds. For e-commerce, writing product descriptions is becoming trivial.

Generative AI Frees you from blank page syndrome and accelerates production. Attention: it produces quality drafts that must be refined by your experts to ensure the relevance and voice of your brand.

Large-scale customization

Of course, personalization improves performance, but don't forget that customizing for each segment requires a lot of work. Again, generative AI can be of great help to you because it makes mass customization technically and economically viable.

Imagine an email campaign with 1000 custom variants automatically generated according to the customer profile in Dynamics 365. AI adapts tone, examples, and arguments based on industry, business size, and centralized purchase history in Dataverse.

Integration with Dynamics 365 Customer Insights makes it possible to combine behavioral data and content generation for a unified and efficient customer relationship. The result: every interaction is relevant without multiplying efforts. Personalized campaigns generally show higher open and conversion rates than traditional generic campaigns.

Creative analysis and insights

Your customers are constantly talking to you through reviews, surveys and social networks. This wealth of information remains untapped because analyzing it manually would take weeks. Generative AI democratizes access to insights by allowing you to query your data in natural language.

Put in a situation, your marketing director asks Copilot: “Analyze our last 500 customer reviews and propose 3 areas of campaign”. In 30 seconds, she gets a summary identifying emerging trends and positioning opportunities through data visualization.

Sales and trade opportunities

Qualification and intelligent prioritization of leads

When it comes to the time your salespeople spend on leads, generative AI is transforming your CRM from an input tool into an intelligent sales assistant.

Copilot for Sales automatically analyzes all interactions: emails, calls, documents consulted, web behavior. It generates instant summaries that give the full context in seconds instead of 30 minutes of research.

Beyond demographic criteria, AI detects Weak buy signals — these subtle signs of buying interest — such as a prospect who mentions a transformation project or frustrations with their current solution. According to Microsoft studies, this approach makes it possible to significantly reallocate salespeople's time to activities with high added value.

Preparing and customizing business interactions

Preparation makes the difference between an appointment that converts and one that is stagnant. Generative AI allows each salesperson to be as well prepared as a top performer.

Before an important appointment, Copilot can automatically prepare a brief :

• information about the target business;
• LinkedIn profiles of participants;
• sectoral issues;
• 3 angles of approach based on similar deals won.

After the appointment, Copilot generates a summary and offers a personalized follow-up email. The salesperson adjusts and sends in two minutes instead of 20. Preparation time can thus be reduced by up to five times in some contexts.

Optimization of negotiation and closing

Some salespeople know how to respond brilliantly to objections, others less so. Generative AI helps to use collective experience to make it an advantage in the service of individuals.

In this respect, Copilot analyzes the patterns of won versus lost deals and identify the real objections behind the apparent objections. The tool suggests structured answers with numerical case studies.

In addition, the generation of value proposals adapts to the decision-making profile: ROI for a financial director, productivity gains for an operational director.

Customer service and support opportunities

Automated and assisted resolution of requests

When your teams spend too much time looking for information, generative AI can allow them to focus on empathy and complex resolution.

Copilot for Service automatically analyzes the complete context: customer history, products owned, previous incidents. In a few seconds, it offers a personalized response that the operator then only has to validate and adjust.

Intelligent chatbots form the first filter of customer requests that they will process by understanding the context of each situation. For the simplest cases, the resolution is autonomous and instantaneous.

According to the observations of several consulting firms, the average processing time can decrease by 30 to 50% depending on the case, while customer satisfaction improves.

Enrichment of the knowledge base

Is your knowledge base incomplete or out of date and no one has time to maintain it? Generative AI uses each solved ticket as a reusable knowledge asset.

For example, the system detects that the same question was asked 10 times this month. After which, it generates a structured article based on the resolutions of your best agents, identifies the appropriate keywords and submits it for validation while guaranteeing documentary traceability. In short, you capitalize on collective expertise in a few clicks.

Sentiment analysis and proactivity

Finally, when a customer tells you they're leaving, it's often already too late. Generative AI you Alert to the first signs of dissatisfaction.

Automatic detection analyzes the feeling in all interactions. So, A customer who uses increasingly frustrated language triggers an alert, allowing intervention before the situation escalates.

This approach also works at scale: identifying trends makes it possible to act at the systemic level. If 5 customers mention the same bug this week, your dashboard alerts you immediately for a numerical escalation to the product team.

HR and talent management opportunities

Recruitment and onboarding: from administrative to human

Contextual CV analysis goes beyond keyword detection. AI includes atypical careers and identify transferable skills. A recruiter analyzes 200 resumes in minutes, identifies the 15 most relevant profiles with justification, and focuses on interviews. Screening time can be reduced by up to ten times in some highly automated contexts, while helping to reduce the risk of missing out on the right candidate.

Once recruited, the right people need to be integrated effectively. Virtual assistants respond instantly to the practical questions of new hires in a modern collaborative environment: leave requests, templates, contacts. The newcomer quickly becomes autonomous without overloading the teams.

Development and commitment: supporting everyone's growth

Beyond recruitment, generative AI improves development support, for which managers often lack time.

In fact, the generation of individual development plans combines current skills, aspirations, team needs and available training. In seconds, the manager gets a structured plan over 6 months. What used to take half a day takes a few minutes.

Likewise, writing constructive feedback is becoming more accessible. AI helps to formulate feedback in an empathetic and actionable way, with concrete recommendations. The objective is not to replace the manager's judgment, but to give him the tools to communicate better, with the final responsibility always remaining human.

How to successfully adopt generative AI in your organization

Identify your quick wins and priority use cases

Faced with all these opportunities, there is a great temptation to want to do everything at the same time. It is the mistake not to make. The key to success is choose use cases with high value AND a high probability of success.

The selection criteria must cross three dimensions:

• The business value (time saved, revenue generated);
• The technical feasibility (available data, integrable systems);
• The probability of adoption (users ready, change acceptable).

Avoid the”Boil the Ocean“(wanting to change everything right away). Start small, prove the value, learn, then expand. A successful pilot project is better than a failed deployment that burns your trust.

With that in mind, a discovery workshop with your teams and an expert partner like Askware makes it possible to quickly identify your 3 priority use cases and to build a realistic roadmap.

AI Security, Governance, and Ethics

Generative AI raises legitimate questions of safety and ethics, but if it is properly framed, generative AI does not present risks.

With the Microsoft ecosystem, as part of professional offerings, your data stays in your Azure tenant, is never used to train public models, and complies with the GDPR for controlled IT compliance. What's more, Entra ID access controls also apply to interactions with AI.

That said, vigilance is still required. AI's “hallucinations” are a reality: it can invent plausible but false facts. Human validation remains absolutely essential on any critical content. The role of AI is to generate drafts, that of the expert is to validate.

As for governance, it defines who can use what and how. Thus, clear policies avoid excesses while allowing innovation.

At Askware, we believe that generative AI should augment humans, not replace them. It is a tool at the service of business expertise, never a substitute for human judgment.

Change management and skills development

Technology is an enabler but it is human adoption which is the only factor of success. Indeed, the best tool doesn't create value if no one uses it.

Start by training your teams in the right uses. You need to help them understand what AI does well, what it does less well, and how to formulate effective instructions. The “Prompt Engineering” — the discipline of structuring instructions to maximize the quality of responses — makes all the difference.

The creation of AI ambassadors in each department accelerates dissemination. These champions identify relevant use cases, test functionalities, and support their colleagues. They create a peer-to-peer support network that is more accessible than the IT team.

Finally, establish a culture of experimentation with a right to make mistakes encourages innovation. Teams should feel free to test and learn without fear of sanctions. A 3-month adoption program with training, user challenges, and celebration of gains transforms initial distrust into enthusiasm.

With Microsoft Copilot and Azure OpenAI, generative AI technologies are accessible, secure, and integrable into your existing processes.

Askware helps you identify your quick wins, build your adoption strategy, and deploy generative AI at the service of your businesses with an approach that balances technological ambition and operational pragmatism.

Let's explore your AI opportunities together: Request your discovery workshop.