Top 7 Trends to Watch in 2025

1. Increased CRM Adoption

Trend: Businesses will adopt AI-powered CRM platforms CRMs more than ever to streamline operations, improve customer management, and drive data-driven strategies. This shift will position CRMs as a foundational tool for scaling personalized customer experiences.

Key Drivers:

• Need for real-time customer insights and predictive analytics.
• Demand for integration across sales, marketing, and service teams.
• Need for more meaningful customer engagement

Examples:

• Zoho AI sales assistant, Zia: Help you predict the probability of conversion for leads or opportunities so you know what to prioritize
• Microsoft Dynamics 365 Copilot: Create journeys using AI assistance

Why This Matters:AI reduces manual data entry, improves customer retention, and enables personalized engagement at scale.

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2. AI Integration in Business Strategies

Trend: AI will transition from a niche tool to a core business driver, embedded in decision-making, operations, and innovation pipelines.

Key Drivers:

• Pressure to cut costs and boost efficiency in competitive markets.
• Need for predictive insights to mitigate risks (e.g., supply chain disruptions).
• Democratization of AI tools for non-technical teams.

Examples:

• IBM Watson Watson optimizes supply chain logistics for retailers by predicting demand, identifying bottlenecks, and recommending cost-effective solutions .
• Siemens integrates AI into its manufacturing processes to predict equipment failures before they occur.

Why This Matters: AI integration future-proofs organizations, enabling agility, innovation, and data-driven leadership.

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3. AI Agents in Workforce and Operations

Trend: Companies will begin integrating AI agents into their operations like customer service, data analysis, and administrative support tasks.

Key Drivers:

• Labour shortages and rising operational costs.
• Advances in agentic AI (self-improving systems).
• Demand for 24/7 customer support.

Examples:

• MindStudio: Build AI Workers and workflows, transforming businesses of all sizes.
• Freshworks Freddy: AI Agent to Improve the Customer and Employee Experience

"The IT department of every company is going to be the HR department of AI agents in the future." Jensen Huang, NVIDIA CEO.

“2025 will be the year when it becomes possible to build an AI engineering agent that has coding and problem-solving abilities of around a good mid-level engineer.” Mark Zuckerberg?, Meta

Why This Matters: AI agents reduce human error, lower costs, and scale operations exponentially

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4. AI-Driven Ad Campaigns and Video Production

Trend: More brands will explore AI tools for ad campaigns, using them to conceptualize, design, and optimize videos. These tools will allow brands to produce high-quality, data-informed content that resonates with target audiences while saving time and costs.

Key Drivers:

• Shortened campaign lifecycle and demand for rapid iteration.
• Budget constraints requiring cost-effective content creation.
• Data-driven personalization to create hyper-targeted ads, improving engagement and conversion rates.

Examples:

• Google’s Performance Max: Uses AI to optimize ad creatives across Google’s platforms (Search, Display, YouTube)
• Runway ML: Generative AI for instant video editing and effects.
• Persado: AI crafting emotionally resonant ad copy.
• Synthesia: Creates AI-generated video content with virtual presenters, eliminating the need for actors, cameras, and studios.

Why This Matters: AI democratizes high-quality content creation, enabling smaller brands to compete with enterprises.

5. AI Models/Avatars in Brand Campaign Videos

Trend: Virtual influencers and AI-generated models will become prominent in brand campaigns, offering creative flexibility and cost efficiency.

Key Drivers:

• Demand for always-on, scandal-free brand ambassadors.
• Need to resonate with Gen Z’s digital-first preferences.
• Cost savings: It will make high-quality campaigns accessible to smaller brands.

Examples:

• D-ID: Animated AI avatars for personalized video campaigns.

Why This Matters: AI models eliminate talent costs, enable limitless creativity, and ensure brand consistency.

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6. Video Content on LinkedIn

Trend: LinkedIn will see a surge in video content as brands and professionals tap into their audience with authentic, relatable, and engaging storytelling, further bridging the gap between B2B and B2C content.

Key Drivers:

• Rising demand for “humanized” B2B marketing.
• LinkedIn’s algorithm favouring native video over text.
• Rising popularity of short-form video

Examples:

Same content, two formats: one as a carousel, the other as a video. The difference? Video significantly outperformed the carousel.

?? Performance Breakdown:

Carousel Post

• 459?Impressions
• 203?Members Reached

Video Post

• 6,904?Impressions (15x more!)
• 5,870?Members Reached (28x more!)
• 1,532?Video Views
• 6h 12m 57s?Total Watch Time

Key Takeaways:

1. Video content drives higher reach and engagement.
2. People spend more time on videos compared to static posts.
3. LinkedIn’s algorithm favours videos, amplifying visibility.

Why This Matters: Video humanizes brands, builds authority, and drives meaningful connections in a professional context.

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7. Hyper-Personalized AI

Trend: Businesses will increasingly prioritize customized AI solutions tailored to their unique workflows, preferences, and objectives. The era of one-size-fits-all AI tools will fade as users demand models that align with their specific needs, driving a shift toward user-centric AI ecosystems.

Key Drivers:

• Task-Specific Optimization: Users want AI tools that excel at niche tasks (e.g., coding, content creation, data analysis) rather than generic platforms. Custom AI models deliver precision and efficiency for specific use cases .
• Personal Branding: Professionals and creators are using personalized AI to reflect their unique voice, style, or expertise.
• Integration with Existing Tools: Demand will grow for AI that integrates with proprietary software, databases, or workflows (e.g., AI trained on a company’s internal data).

Examples:

• Custom GPTs (OpenAI) and Amazon Q (AWS’s business-focused AI) allow users to build task-specific AI agents.
• Startups like Hume AI focus on emotionally intelligent AI tailored to individual communication styles.

Why This Matters: Personalized AI reduces friction in adoption, improves efficiency, and fosters trust by ensuring outputs are relevant, accurate, and aligned with user goals.