AI for Risk Management: Comparing Alternatives

The integration of artificial intelligence into risk management is changing the way companies predict, analyze, and mitigate uncertainties.

By applying AI, it is possible to increase the accuracy of risk assessments while also improving forecasting and planning capabilities.

Among the most widely used tools for this purpose is of course Microsoft Copilot, but it is not the only one.

In this article, we will compare the best AI tools for risk management, looking at their features, advantages, and limitations, to understand which is the most suitable for your company.

AI for risk management: a brief introduction

Adopting risk management strategies based on artificial intelligence can provide a competitive advantage by enabling organizations to anticipate and mitigate potential threats, improve decision-making accuracy, and protect assets and operations.

AI is therefore becoming a key element in the development of solid risk management strategies across different industries.

According to recent market studies, the value of the AI reliability, risk, and security management market was 1.7 billion dollars in 2022 and is expected to reach 7.4 billion dollars by 2032, with a compound annual growth rate (CAGR) of 16.2%. This significant growth highlights the value that artificial intelligence brings to identifying and managing business risks.

This is thus a rapidly growing and highly competitive market, where development companies from all over the world are striving to carve out their share with AI-based solutions.

Among these companies, Microsoft could not be absent.

With its Copilot, the company has managed to establish its digital assistant as one of the leading solutions on the market, competing with software giants such as Google and OpenAI, the pioneer of commercial Gen AI as we know it today.

But is Copilot the best solution among those available?

What are the alternatives and how do they compare with Microsoft’s AI?

We will explore this in the following sections.

What is Microsoft Copilot

Before going into detail, let’s take a moment to briefly introduce Microsoft’s AI assistant.

Microsoft 365 Copilot helps simplify and initiate knowledge-based routine tasks commonly performed by people. According to Microsoft, Copilot works alongside users, integrating into the Microsoft 365 applications they use every day.

It is designed to become part of users’ daily workflow, helping them perform repetitive and routine tasks faster and more efficiently, while offering significant benefits. For example:

It allows users to save time on repetitive activities by automating follow-ups, taking meeting notes, generating summaries, creating presentations, and more.
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It enables interaction with systems through natural language input, such as writing complex formulas in Excel.
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It can provide data analysis faster than a human (although accuracy must still be verified).
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It is accessible across all Microsoft 365 applications, potentially becoming the new default interface for interacting with them.
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It facilitates content creation and iteration, brainstorming, and the development of new ideas.

Microsoft 365 Copilot can generate responses based on a company’s organizational data, such as user documents, emails, calendar, chats, meetings, and contacts. When activated, Copilot can combine this content with the user’s current work context, including ongoing meetings, email exchanges, and chat conversations.

It can be used to create documents, presentations, spreadsheets, notes, emails, and more. However, to access it, a company must have a Microsoft 365 E3, E5, Business Standard, or Business Premium subscription, at a cost of about 30 dollars per user per month.

There is no minimum license requirement, so Copilot can be enabled even for organizations with only a few dozen users. Finally, the company’s IT department must activate its use within corporate systems.

Regardless of the application where generative AI is integrated, Copilot offers:

Summaries based on text and other resources.
Content generation based on user prompts.
Analysis and consolidation of information from different sources, such as notes, emails, documents, presentations, Excel spreadsheets, and company repositories.

The specific use of these features varies depending on the Microsoft application.

Copilot uses Microsoft’s Prometheus AI model, which leverages OpenAI’s generative AI tools, including ChatGPT-4, ChatGPT-4o, and DALL·E 3.

Normally, accessing these tools in ChatGPT would require a ChatGPT Plus subscription, whereas with Copilot they are included at no extra cost.

In addition to OpenAI models, Prometheus uses:

Bing’s web search database.
Microsoft Natural Language Processing.
Text-to-Speech for realistic voice responses.
Azure Cloud Services for scalability and reliability.
Retrieval Augmented Generation to enhance response context.

The main competitors of Copilot in risk management

Now that we have presented Copilot, it is time to introduce its biggest rivals in the AI risk management market.

And the names are quite significant.

On one side, there is SAS Institute, with its long history of solutions for business intelligence and corporate risk management. On the other, the legendary Palantir, founded by Peter Thiel, which has become a powerhouse in the government sector and is now seeking to expand into the broader business market.

These are giants that Microsoft has faced head-to-head many times before, and naturally, another clash was bound to happen in the AI market as well.

Let’s take a moment to get to know these competitors and examine their strengths and limitations.

SAS Viya

SAS Viya is a cloud-native, open analytics platform developed by SAS Institute, a company renowned for its analytics and business intelligence solutions. It represents a significant step forward compared to its predecessor, SAS 9, thanks to the adoption of modern technologies and methodologies that provide enhanced analytical capabilities.

The platform offers a unified and scalable environment to perform a wide range of analytical tasks, enabling organizations to tackle complex challenges and extract valuable insights from their data.

Although not strictly a digital assistant, the platform includes numerous AI-driven features, making it a viable option for large enterprises looking to make significant investments in the latest advances in Machine Learning and GenAI.

Key strengths of the SAS solution

Strengths	Description
Advanced analytics	SAS Viya offers a comprehensive suite for predictive analytics, machine learning, and deep learning, with algorithms optimized for risk management. Its modeling capabilities enable forecasting of scenarios and behaviors, supporting decisions based on concrete data and advanced simulations.
Data integration	It is designed to aggregate and harmonize data from internal and external sources, both structured and unstructured, in order to create an integrated view of the company’s risk profile. This leads to more accurate and reliable assessments.
Transparency and governance	The platform enables strict governance of analytical models: every output is traceable, auditable, and documentable—essential qualities to meet regulatory compliance requirements and ensure trust in decision-making processes.
Cloud-native scalability	Flexible cloud architecture that allows scalable use of computing resources in both public and hybrid cloud environments. This makes it possible to support organizations with high volumes of data and complexity.
Regulatory compliance	SAS Viya is used by institutions subject to strict regulations (e.g., banking and insurance sectors) thanks to its built-in support for standards such as Basel III, IFRS 9, CECL, and other risk management frameworks.

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Like any market solution, however, Viya also has its limits and challenges.

Main limitations of SAS Viya

Limitation	Description
Technical learning curve	Despite the visual interface, effective use of advanced features requires statistical and programming skills, limiting the autonomy of business teams.
Implementation time	Implementation can take a long time, especially in organizations with complex architectures or strict regulatory requirements.
Total cost of ownership (TCO)	The combination of licenses, infrastructure, and specialized services can generate a high TCO, making the solution less accessible for organizations with limited budgets.
Dependence on SAS environments	The solutions are highly optimized for the SAS ecosystem, which can make interoperability with modern non-SAS or third-party cloud-native IT environments more difficult.
Collaborative experience	Collaborative work and shared access to models require additional tools or specific integrations, slowing down the spread of ERM among cross-functional teams.

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Palantir

Palantir Technologies Inc. is a publicly traded American software company founded by Peter Thiel, specializing in big data analytics. It is best known for its platforms that help organizations integrate, analyze, and interpret large volumes of data.

With the goal of supporting decision-makers in extracting insights from large datasets, Palantir has become a key player in sectors such as public administration, healthcare, and defense.

Although the company’s core business has long been tied to government contracts, expansion into the commercial sector has become a strategic priority, and commercial contracts now represent a growing share of Palantir’s revenues.

The company is positioning itself as a leading player in artificial intelligence through platforms such as Foundry, which integrate machine learning algorithms and AI-driven analytics. Its ability to support organizations in developing decision models and predictive analyses based on artificial intelligence represents one of the main growth areas for Thiel’s company.

Key strengths of Palantir Foundry

Aspect	Extended description
Data integration and fusion	Palantir is designed to aggregate and correlate large volumes of data from heterogeneous sources (ERP, legacy systems, external sources), generating a “digital twin” of the organization that makes the interconnection between events, assets, and risks visible in real time.
Real-time operational analysis	The platform enables situational analysis and immediate response to emerging risks through dynamic dashboards and rule engines. This is particularly effective in contexts where timeliness is critical (e.g., supply chain, security, compliance).
Modularity and adaptability	Palantir is highly configurable: it can be modeled on specific organizational processes and quickly adapted to new regulatory or operational requirements, ensuring flexibility even in complex evolving scenarios.
Collaborative risk management	Integrated workflows allow different business stakeholders to collaborate in risk management, sharing information, decisions, and responsibilities in a transparent way. This supports a shared enterprise-level view of risk.
Security and access control	Designed for highly sensitive environments, Palantir implements a granular authorization system, with differentiated visibility by role, function, and risk level. It is used in mission-critical contexts, including governmental and military.
Contextual and applied AI	Artificial intelligence is not presented as a separate feature but is “embedded” in analytical workflows, helping users interpret anomalies, simulate scenarios, and recommend actions based on the specific operational context.

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Palantir and its Foundry platform therefore represent a formidable competitor, but not without issues and limitations that any company should consider if evaluating it as a viable option.

Main limitations of Palantir Foundry

Limitation	Description
High configuration complexity	The extremely flexible and customizable approach requires in-depth analysis, tailored design, and specialized resources to achieve results consistent with business needs.
Dependence on dedicated technical teams	To effectively manage and update models, workflows, and data, an experienced internal team or dedicated partners are required, slowing down the cross-organizational adoption of the tool.
Significant initial costs	License and onboarding costs can be substantial, especially for companies that do not yet have an aligned IT infrastructure or a consolidated data culture.
Limited self-service adoption	Business users often cannot use the platform independently without targeted training, hindering the democratization of risk management.
Complexity in evolutionary maintenance	The high degree of customization means that each evolution (e.g., regulatory updates or new metrics) must be implemented on a case-by-case basis, with impacts on time and costs.

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The unique advantages of Copilot for risk management

Two major competitors and a market to conquer.

At first glance, Copilot’s mission may not seem easy, but a few clarifications are needed before moving on to a direct comparison.

The most important is a technical distinction: Viya and Palantir Foundry are platforms designed primarily for expert technicians. Their offerings include AI features, but these are not specifically aimed at acting as “digital assistants.”

Copilot, on the other hand, is a digital assistant specialized in helping users carry out their daily tasks. It is a versatile chatbot which, thanks to its deep integration with the entire Microsoft ecosystem, enables non-technical staff and business users to get the most out of Microsoft’s software and unlock its full potential.

That said, if what we are looking for is company-wide assistance in risk management, it is time to compare the three.

Advantages of Copilot over competitors

Feature	SAS Viya	Palantir	Microsoft Copilot
Accessibility and business adoption	Powerful platform but primarily aimed at data scientists and expert analysts. Usage by non-technical staff may require dedicated training.	Offers visual flows and advanced interfaces, but effective interaction requires some familiarity with the system and its data models.	Designed for business users: works directly within everyday apps, democratizing access to AI and risk analysis without the need for specialized skills.
Integration with the enterprise ecosystem	Good integration with other SAS products and support for external connectors, but often requires tailored interventions for complex environments.	Flexible architecture and broad connectivity, but integration with existing IT stacks can involve significant time and cost.	Natively integrated into the Microsoft 365, Azure, and Dynamics ecosystem: drastically reduces adoption times and maximizes the value of technologies already in use.
Analytical and AI capabilities	Provides advanced tools for statistical analysis, predictive modeling, and machine learning with great technical depth.	Includes customizable AI models and logics, ideal for specific and highly complex contexts.	Copilot leverages advanced AI models (including GPT and Azure ML), directly applicable to decision-making processes to identify, interpret, and mitigate risks in real time.
Time-to-Value and implementation speed	Kick-off requires design, configuration, and often dedicated specialist support.	Production deployment may take medium to long timelines due to required customization.	Copilot is immediately operational in Microsoft environments, significantly reducing time-to-value and accelerating return on investment.
Support for collaboration and risk culture dissemination	Collaborative flows are present but often separate from everyday operational tools.	Promotes collaboration on targeted use cases, but cross-functional involvement may require complex orchestration.	Encourages a shared corporate risk culture thanks to native integration within already adopted collaboration channels (Teams, SharePoint, Loop).
Governance, security, and compliance	Robust solution compliant with industry regulations, with strong controls on data and models.	Provides enterprise-grade security and high standards, often adopted in defense/government contexts.	Built on Microsoft Security and compliant with regulations such as GDPR, ISO 27001, NIS2. It also ensures granular management of data and access.
Economic sustainability and scalability	Enterprise solution with a cost model proportional to the complexity of the implementation.	Requires significant investments in licenses, setup, and management, with high costs at scale.	Modular and scalable approach within the Microsoft cloud. Existing Microsoft customers can activate Copilot with marginal impact on TCO (Total Cost of Ownership).

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Conclusions

So what is the verdict?

As mentioned, these are very different solutions. If what we are looking for is an AI assistant that can support our teams and less technical users in their risk management operations at every level, Microsoft Copilot remains the best choice.

Microsoft’s “copilot” is a versatile assistant, deeply integrated with the main daily work tools used by thousands of employees worldwide, and it stands out as one of the best AI solutions on the market in terms of value for money.

Over time, it has rightfully earned the reputation of being the “best productivity tool” of recent years, and Microsoft itself has shown its confidence in the product by implementing it at every level of its organization.

Whether future competitors will be able to dethrone Copilot remains to be seen, but for now Microsoft’s AI assistant continues to be one of the best AI solutions for companies of all industries and sizes.

FAQ on AI tools for risk management

What is AI for risk management?

‍Artificial intelligence applied to risk management enables companies to predict, analyze, and mitigate risks more accurately and promptly. Thanks to predictive models and advanced analytics, AI improves the precision of assessments and the ability to plan effectively.

What is the growth of the AI risk management market?

‍The market for reliability, risk, and security management through AI was valued at 1.7 billion dollars in 2022 and is expected to reach 7.4 billion dollars by 2032, with a compound annual growth rate (CAGR) of 16.2%. This highlights the increasingly central role of AI in risk management.

Is Microsoft Copilot suitable for risk management?

‍Yes. While it is not a specialized platform like SAS Viya or Palantir Foundry, Microsoft Copilot is a digital assistant that integrates AI directly into Microsoft 365 applications. It is particularly useful for democratizing the use of AI in day-to-day risk management, making it accessible to non-technical users.

What are the main advantages of Microsoft Copilot compared to its competitors?

‍Microsoft Copilot stands out because it can be easily used by non-technical staff within everyday work applications such as Excel, Outlook, and Teams, and it is natively integrated with Microsoft 365, Azure, and Dynamics. It is immediately operational in Microsoft environments, significantly reducing adoption time and costs. It also fosters a shared risk culture thanks to its presence across collaboration tools and offers a sustainable pricing model, especially for organizations already using the Microsoft ecosystem.

What are the main alternatives to Microsoft Copilot?

‍Two significant competitors are SAS Viya, a cloud-native analytics platform designed for large organizations with data science teams, and Palantir Foundry, a solution created to handle massive volumes of data and widely used in government as well as increasingly in business. Both offer advanced features but require longer implementation times, specialized expertise, and significant investments.

Can Copilot replace solutions like SAS Viya or Palantir Foundry?

‍Not entirely. SAS Viya and Palantir Foundry are complex platforms designed for expert analysts and highly specialized contexts. Copilot, on the other hand, is aimed at a broader audience, facilitating AI adoption in daily work and improving productivity and distributed risk management.

How much does Microsoft Copilot cost?

‍Copilot is available with Microsoft 365 E3, E5, Business Standard, or Business Premium subscriptions, at a cost of around 30 dollars per user per month. It can also be activated by small companies, with no minimum license requirement.

How can I adopt Copilot to improve risk management in my company?

‍To get the most out of Microsoft Copilot, it is important to evaluate compatibility with your existing IT environment, properly enable licenses, and train users. In this process, specialized partners such as Copilot Circle can support your company at every stage, from technical activation to process customization, and provide the skills needed to achieve a real return on investment.

Giuseppe Marchi

Microsoft MVP

Giuseppe Marchi has been a Microsoft MVP since 2009, focusing on SharePoint, Microsoft 365, and Copilot.

AI for Risk Management: Comparing Alternatives