New research: 6 AI priorities for investment firms

AI is quickly moving from proof-of-concept projects to a foundational part of how investment management firms collaborate, innovate, and evolve. AI-powered platforms for banking and financial services are enhancing operations from the front office to the back office.

Investment management firms have been planting the seeds of AI integration for years, according to new ThoughtLab research sponsored by ServiceNow, FNZ, and Grant Thornton. And the time to move from exploration to enterprise adoption is now.

The research found that 78% of investment firms have been building company cultures that encourage AI adoption, and 77% have put in the work to create an effective AI roadmap.

Global firms are adopting a wide swath of AI models, from generative to agentic. AI in this space is both a mindset and framework that touches all parts of the value chain.

For firms ready to go from theoretical to real-world AI applications, we recommend focusing on six AI priorities to empower the people who interact with the tools daily.

1. Maturity: Going beyond pilots

The research classified respondents into three levels of AI maturity:

• Starters are firms in the early stages of AI implementation.
• Advancers are making progress toward their AI goals.
• Leaders are showing signs of strong maturity.

Leaders have seen much stronger return on investment (ROI) from their AI efforts than other organizations in the survey.

While firms don’t need to be perfectly positioned before integrating AI into their operations, a certain level of maturity can help set up an organization for success.

Investment firms should ensure skill sets, data management systems, and AI roadmaps are in place before forging ahead with AI transformation. This can help enterprises reach a level of AI maturity to take them beyond pilot programs.

2. Governance: Building trust

AI technology brings incredible opportunities—but it also comes with risks. Every industry faces challenges such as data privacy concerns, algorithmic bias, and the potential for system errors. For financial services firms, the stakes are much higher.

Financial institutions operate in a space where precision, trust, and compliance are nonnegotiable. A single flawed algorithm or biased model can lead to major financial losses, regulatory penalties, or reputational damage. For those reasons, AI adoption in finance demands greater care and oversight—and a sharper focus on governance, transparency, and ethical responsibility—than in most other industries.

Fostering trust among clients, boards, and regulators is critical. Organizations can benefit from having appropriate guardrails in place, including:

• Usage policies for all employees
• Data frameworks for storage, sharing, and analytics
• A governance board
• Recurrent training for teams on best practices and regulations

A governance approach can help keep AI in line with a firm’s ethos and protect employees and clients from risk. More than half (59%) of survey respondents agree that industry regulations on AI governance will likely have an impact on their operations in the next three years.

Firms that keep the risk management conversation going internally will be best equipped to manage external regulations as they solidify.

3. An enterprise platform: Removing fragmentation

Investment management firms seeing positive ROI from their AI practices often have a cloud-based IT platform that blends the AI capabilities of their enterprise software and software as a service (SaaS) solutions.

In fact, 53% of firms use an enterprise platform with built-in AI functionality, the research found. Combining AI with powerful enterprise software can boost the capabilities of the full tech stack. Data can be integrated from multiple sources to empower client service, sales, management, and operations to make better-informed decisions.

Onboarding a comprehensive IT operations, risk, and security management platform can help investment firms balance client experience issues such as managing disputes with IT service management. A consolidated platform and dashboard can also help streamline workflows and insights to speed decision-making.

4. Modern workflows: Streamlining operations

With multiple client touch points and global networks to manage, investment management firms often have complex, burdensome workflows to get things done. The more manual effort that’s needed to complete a task, the more time that’s taken from a financial professional’s and a client’s day.

Additionally, investment firms sometimes struggle to scale workflows in client onboarding, compliance, reporting, and trade execution. When this happens, it affects all areas of the business.

Firms that are ready to tap the power of AI workflows should look beyond automation for the biggest impact. AI that can manage menial tasks is certainly useful, but AI that can make decisions and drive processes is transformational.

Several leaders in our research referenced agentic AI use cases such as creating investigative workflows and managing complex client service tasks with minimal human intervention.

The key to success is to build workflows that are “outcome-focused rather than prescriptive” and move from a digital mindset to an AI one, says ServiceNow Chief Innovation Officer Dave Wright. Developing that mindset may require a culture shift.

That culture change can help firms balance getting work done, elevating customer service, and maintaining data integrity.

ServiceNow on Amazon Web Services (AWS) unites AI, data, and workflows across the enterprise. This helps deliver transformative value for investment firms by streamlining operations, enhancing compliance, and accelerating AI-driven decision-making.

5. Innovation: Building vision together

Company culture has an outsized impact on a firm’s ability to innovate. Leaders in our research reported their “slow-moving, conservative culture” has hindered innovation efforts (55%), their team has limited AI skill sets (45%), and their organization sees employee resistance to AI adoption (42%).

All departments at a firm, from IT to sales, should be involved in developing AI frameworks.

According to Chris McDonald, capital markets industry specialist at AWS, generative AI-powered dashboards are a key area of growth for connecting advisors and the broader firm. dashboards are a key area of growth for connecting advisors and the broader firm.

“These systems are revolutionizing pre-meeting intelligence gathering, reducing what once took hours to just minutes,” he explains. “They're also identifying client retention risks through sophisticated pattern recognition in behavior and market conditions, enabling more proactive and timely client engagement.”

Innovation is a team sport. Building a clear vision together, and offering AI skills development opportunities, will create AI evangelists across the organization. You’ll want those internal advocates when it’s time to roll out new tools and processes.

6. Urgency: Embracing change

AI is a major catalyst for change in the investment management industry. Firms that act now will define the next decade of financial services.

Leading firms in our research offer a few best practices for jumping in:

• Put people at the center of your AI strategy, focusing on employee productivity and client retention.
• Consistently measure strategic impacts and the efficacy of your AI solutions.
• Play the long game.

Gain more insights in our ebook: The AI-Powered Investment Management Firm.