AI Evolution blog explores a wide range of topics tailored for operational leaders and innovators, including:

AI Market Analysis: Periodic reviews of market trends and the evolving AI landscape.
AI Research Insights: Relevant topics around traditional machine learning, models, LLMs, GenAI, agents, algorithms, deep learning, neural networks, agentic software and much more.
AI Product Innovation and Strategy: Relevant topics around product development, economics, and go-to-market (GTM) strategies.
AI Software Engineering Lifecycle: Best practices for developing, testing, and managing AI-enabled and AI-native products.
Adopting AI Across Enterprise: Strategies to boost operational efficiency through AI adoption.
And much more, offering relevant insights to keep you ahead in the AI-driven world.

Leading Compliance and Security in the Age of AI

If you are a leader in charge of compliance and information security for your organization, you’ve likely encountered the one-line, yes-or-no question in board meetings: "Are we compliant and secure?". As businesses increasingly embrace AI, the question evolves: "What is our strategy and roadmap to support AI adoption securely and compliantly?"

The rapid adoption of AI brings both opportunities and challenges, and compliance and security teams must grapple with several common scenarios:

Common Scenarios Facing Compliance and Security Teams

AI Features in Existing Tools: Your IT teams need to understand the implications of enabling AI features in corporate software tools like Salesforce, Microsoft 365, SAP, Workday, Oracle etc used by multiple functions within enterprise. They also need guidance on adopting new AI tools and vendors, such as ChatGPT or modern AI-driven content marketing tools.
Data Usage: Your data teams might require guidance on the use of datasets within the organization or sourced from third parties to train machine learning models. They need to understand potential compliance issues and ethical considerations.
IP protection: Need to balance the adoption of AI by many functional areas, while protecting the enterprise and product data. Guidelines need to be developed and provided to various stakeholders as they expose sensitive data to tools and their party of software.
Third-Party Integration: Your product teams are evaluating the integration of third-party products into your offerings to deliver AI-powered features. They need clarity on the compliance risks and security implications.
Third-Party or Open-Source Libraries: Your technology teams want to leverage third-party or open-source machine learning libraries to build software. Assessing the risks associated with these resources is critical.
Board-Level Assurance: Leadership and the board demand a straightforward, yes-or-no answer to whether the organization is secure and compliant in the age of AI.

While the answers often depend on the industry, especially for highly regulated sectors like healthcare, the underlying question remains: How can we preemptively address data and security breaches resulting from AI adoption?, In some cases, How to we protect/prevent outside parties using our IP/Data without our knowledge?.

Critical Steps to Strengthen Security and Compliance for AI

Here are high-level steps organizations must take to address these challenges:

Enhance Your Security Strategy and Roadmap: Security strategies must evolve to explicitly address data and AI. Compliance and security frameworks should include controls tailored to AI risks, such as model integrity, data provenance, and algorithmic transparency.
Educate Compliance Teams on Data and AI: Compliance teams must develop a deep understanding of AI-related risks and opportunities. Creating clear, actionable policies on intellectual property protection, data ethics, privacy, and regulatory compliance will enable them to guide both internal and external stakeholders effectively.
Update Security Playbooks: Security teams should revise their playbooks to incorporate AI-specific policies and controls. This includes guidelines for software development, testing, deployment, and monitoring, as well as operational safeguards for AI systems.
Foster Collaboration Between Security ,Compliance and Operating Teams: To adopt AI safely and ethically, security and compliance teams must work closely with operational teams. Proactive collaboration can help identify and mitigate risks before they become issues.

Leading the AI Journey in 2025

In 2025, security and compliance teams need to lead from the front. They must become equal stakeholders in the organization’s AI journey, shaping policies and strategies that enable safe and ethical AI adoption. By addressing compliance and security holistically, these teams can ensure AI becomes a driver of innovation rather than a source of risk.

We invite you to learn from our real-world experience in developing and executing AI strategies, and discover how we can support your organization's AI journey.

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Security, Compliance, Product, Engineering, TechnologyBlackPepper LabsJanuary 27, 2025

One of the early use cases of Generative AI has been around, how to create, manage and operate Agents for supporting existing customers. As you might have noticed, Salesforce has been promoting AI agents in their platforms, so do other providers like Servicenow, Zendesk. Naturally it is the extension of their business model to protect existing business from over AI optimization, while making sure a their version of AI narrative is promoted. However there are plenty of AI-First agent products have been coming to market in 2024. We have seen good adoption of these agents in enterprise context.

As these technologies mature, a crucial conversation has emerged around leveraging AI for end-to-end customer support and success. This includes new customer onboarding to providing product support(including tech support in most cases).

So, if you are a Chief Customer Officer or Leader in this organization, naturally you have to be able to create Ai strategy to adopt agentic software capabilities. In most organizations, these capabilities are provided by IT function. However it is crucial to be able to understand and create your own strategy around AI for your department beyond toolings. Following are crucial points that keeps coming up in conversations between Exec Leadership and Chief Customer Success office.

"How can we leverage AI Agents to best support to customers to make them successful?"

"What's the fastest path to optimize existing customer support systems and data?"

"How can we increase key KPIs such as NPS and CSAT while optimizing customer success/suport investments?"

"How do we maximize our existing talent's efficiency?"

"Which current Gen AI/Agent tools can deliver immediate productivity gains?"

While these questions are critical, the answers vary significantly based on organizational role and AI expertise. This has created three distinct stakeholder groups:

1. Investors, particularly in PE and VC spaces, seeking efficiency gains in customer success and support budgets beyond offshoring.

2. Organizational leaders driving acceleration and digital transformation initiatives need to show ROI backed by key metrics including efficiency gain metrics

3. Product Support, Success and onboarding leaders tasked with adoption, and implementation

For those in the third category, the responsibility is significant. Success requires crafting both short and long-term strategies through careful discovery, stakeholder education, and adaptive road mapping - all while navigating this rapidly evolving technological landscape collaborating with technology function.

The challenge isn't just about adopting new tools - it's about understanding their true potential and limitations in your specific customer success, product and operational context. As we move forward, the winners won't be those who simply embrace AI, but those who strategically integrate it into their customer lifecycle managment processes while maintaining focus on business outcomes.

We invite you to learn from our real-world experience in developing and executing AI strategies, and discover how we can support your organization's AI journey.

AI Evolution - Blog

Leading Compliance and Security in the Age of AI

Common Scenarios Facing Compliance and Security Teams

Critical Steps to Strengthen Security and Compliance for AI

Leading the AI Journey in 2025

Learn More

Learn More