AI in FS: Is your focus in the right place?

Now that you have established where the push for implementing the new technology comes from, it’s time to assess where you’re at in the change process. Different players in the landscape are going to adopt AI at different speeds. There will be laggards, leaders, and winners. The slowest will be those who underestimate the impact of AI. The leaders are those who are already actively exploring and adopting AI solutions. And the winners will be those who are strategically investing in AI to gain a competitive edge. Which one are you? Use our guide below to assess where you’re at on the journey.

Laggards

Believe that…:

• …AI is something that will create impact but feel it is another hype curve
• …it is enough to focus on the functional threats, ignoring the foundational and existential ones
• …there is no need to invest holistically

Actions / Consequences:

• Silos of experience and expertise
• Pockets of value and benefit are created through chance, and not at a high-enough level to make a difference across the organization
• A culture of prevention and risk aversion rather than adoption
• A talent leak as people fear they are falling behind

Leaders

Know that…:

• …they should be consuming AI services in commercial off-the-shelf and off-the-shelf (COTs and OTS) solutions
• …they need to consider AI and automation in every process and role to look for efficiency and cost reduction
• …this is just the beginning of a broader change and adoption program, and it needs to be thorough and swift
• …there are risks both from legislation and third-party copyright infringement and bias

Create…:

• …centers of excellence (CoE) and innovation communities to create the models for change and adoption
• …communities of change champions and early adopters
• …a culture of AI for everyone, in everything, everywhere

Winners

Appreciate that…:

• …once GenAI is adopted, there is no going back, at least in terms of process automation and intelligent and skilled task automation
• …the customer may change expectations drastically in a very short period
• …there needs to be serious investment in multiple areas of the business, including new service and product development, to service the AI-enabled customer and respond to the competitor
• …they need to be brave and get ahead, even if some efforts are a “dead end”

Create…:

• …everything the Winners have
• …develop incubators, labs, and digital company replicas to safely predict how new processes or technology will affect the organization
• …multi-faceted change programmes

Next, we’ll take a look at some real-world use cases that showcase the power of AI. The best use cases come from a firm understanding of your organization's technology and data capabilities while simultaneously tailoring use cases that will boost key KPIs and further strategic objectives.

Use case #1: Investment advice 

Moody’s Research Assistant leverages proprietary content and LLMs to help clients generate new insights from an extensive library of credit research, data, and analytics to:

• Rapidly generate credit memos and compile custom reports
• Acquire the latest relevant information, including current live ratings changes and research
• Provide linked citations

Business outcomes
Based on findings during the pilot period, users were able to save up to 80% of the time spent on data collection. The assistant reduced time spent on analysis by up to 50%, and could save users up to 27% of the time spent performing the tasks and functions of a financial analyst.

Use case #2: Automated client contact

Klarna’s AI customer service expert services refunds, returns, payments-related issues, cancellations, disputes, and invoice inaccuracies. Features include: 

• 24/7 customer service
• multilingual chat support across 35 languages and 23 markets
• real-time updates on outstanding balances and upcoming payment schedules 

Business outcomes
The AI expert provides a clear understanding of customer purchasing power and justification of spending limits. In addition, it completes the work of 700 full-time agents, engaging in 2.3 million conversations - equivalent to two-thirds of Klarna’s customer service chats. Customer satisfaction was on par with that of human agents, and the AI’s accuracy in errand resolution resulted in a 25% drop in repeat inquiries. It also reduced errand resolution time from 11 mins to 2 mins, leading to an estimated $40M USD in profit improvement in 2024.

Use case #3: Deeper client insights

InMoment securely and intelligently transformed hundreds of pieces of individual and discrete feedback into easily consumable, short, structured paragraphs to surface the most important topics and trends to help organizations take immediate action on customer feedback. 

This example leveraged OpenAI’s GPT technology to predict customer intent and identify whether a customer intends to buy, quit, recommend, or discourage business. InMoment’s Active Listening conversational bot uses real-time text analytics to listen, understand, and respond - eliciting more valuable data points to understand customer feedback.