Why an AI FAQ?

Executives, managers, and entrepreneurs often face the same questions when considering artificial intelligence. What is AI exactly? How much does it cost? Will it replace jobs? How do we ensure it’s ethical? A Frequently Asked Questions resource brings clarity, busts myths, and provides practical answers grounded in real-world consulting experience.

Top Questions About AI

1. What is artificial intelligence?

Artificial intelligence refers to systems that can perform tasks normally requiring human intelligence, such as understanding language, recognizing patterns, making predictions, or learning from data. AI spans techniques like machine learning, deep learning, and natural language processing.

2. How is AI different from machine learning?

AI is the broad field of creating intelligent systems, while machine learning is a subset focused on algorithms that learn from data. Deep learning is a further subset of machine learning, using neural networks to handle large, complex data.

3. How much does it cost to implement AI?

Costs vary widely. A simple AI pilot might cost under $50,000, while enterprise-scale deployments can run into millions. The key is aligning investment with ROI, starting with pilots before scaling.

4. What industries benefit most from AI?

Finance, healthcare, retail, manufacturing, logistics, and energy see strong ROI from AI. But all industries — including education, government, and non-profits — can benefit if data is leveraged effectively.

5. Does AI replace jobs?

AI automates tasks, not entire jobs. Most organizations see job roles evolve: repetitive tasks shrink, while new opportunities in oversight, strategy, and innovation grow.

6. How do we measure ROI from AI?

By setting clear KPIs before projects begin. Examples: reduced processing time, higher customer satisfaction, lower error rates, increased revenue. ROI comes from efficiency gains and new value creation.

7. What is data readiness?

Data readiness refers to the quality, accessibility, and governance of data. AI models are only as good as the data fed into them, so audits and preparation are essential before launching projects.

8. How long does it take to implement AI?

Pilots can be designed in 6–8 weeks. Full-scale deployment may take 6–12 months depending on scope, data complexity, and change management needs.

9. What risks come with AI?

Key risks include bias in data, security breaches, compliance violations, and lack of adoption by staff. Strong governance frameworks mitigate these risks.

10. What is AI governance?

AI governance is the set of policies, processes, and oversight mechanisms ensuring AI is used responsibly, ethically, and in compliance with regulations.

11. How can small businesses use AI?

SMBs can leverage off-the-shelf AI for tasks like marketing automation, customer service chatbots, or analytics. For competitive edge, they can also adopt custom AI solutions scaled to their budget.

12. How does Active AI help businesses?

Active AI provides consultancy services, readiness assessments, and custom solutions. We help businesses move from strategy to pilots to full-scale deployments with ongoing support and optimization.

13. What’s the difference between AI consultancy and hiring freelancers?

Consultancy ensures structured, ROI-driven projects with accountability, governance, and expertise across strategy and technical delivery. Freelancers may lack oversight or continuity.

14. How does AI affect compliance?

AI systems must respect data privacy laws (GDPR, CCPA, Loi 25 in Quebec). Active AI integrates compliance and ethical design into every project.

15. Can AI be biased?

Yes. Bias can occur if training data reflects inequalities or errors. Governance, bias audits, and diverse datasets are critical to reducing risks.

16. What’s the future of AI?

Expect AI to become more embedded in daily business operations, powering decision support, automation, and personalized customer experiences. Regulation and ethical design will grow in importance.

17. How do we get started with AI?

The first step is an AI readiness assessment to evaluate your data, infrastructure, and use cases. From there, design pilots that align with business priorities.

18. Can AI be integrated with existing systems?

Yes. Modern AI solutions can integrate with CRMs, ERPs, cloud services, and legacy systems through APIs and middleware.

19. Do AI projects always succeed?

No — up to 70% of AI projects fail without structured processes. Active AI reduces this risk with governance, pilots, and continuous optimization.

20. How do we train employees for AI?

Through workshops, training sessions, and change management programs. AI adoption is as much about people as technology.

Next Steps

AI raises many questions — but the answers are clearer with the right partner. Active AI provides guidance across strategy, implementation, governance, and optimization. Whether you’re exploring pilots or scaling enterprise-wide, we ensure AI adoption is responsible, practical, and ROI-driven.