Artificial Intelligence (AI) is shaking things up in Strategic Response Management (SRM). Some businesses are just starting with AI, others have strict limitations, and many are already using it daily. Even with these different levels of use, AI is set to transform how organizations share information with customers and prospects with unprecedented speed, accuracy, and efficiency.
AI streamlines SRM, reducing risks and easing employee workloads. In an environment where buyers are asking more questions than ever before and competition has never been fiercer, AI is a real game-changer. AI is no longer just a luxury tool; it’s becoming essential for creating value and achieving operational excellence.
Responsive CEO and Co-founder Ganesh Shankar was recently invited to take part in the 1ArtificialIntelligence 2024 Global AI Conference, where he spoke with Responsive Advisory Board member and EVP of Growth Strategy at Green Thread Stephen Diorio.
Shankar shared his insights on how AI can transform customer response processes, the evolution of AI algorithms and their continued scalability, as well as future directions and practical steps businesses can take now to get started with AI in SRM.
Here are the highlights.
What is AI-driven Strategic Response Management (SRM)?
For those unfamiliar with the term, Strategic Response Management (SRM) is a new way to approach customer responses and the sharing of organizational knowledge, including formalized questionnaires (e.g., RFPs, DDQs, VSQs, etc.), proactive proposals, and even ad hoc communication like email. SRM is defined as the people, practices, and technology that unlock organizational knowledge for profitable growth.
“In my experience, in terms of applying AI to create value in 2024, I believe responding to customers and answering their questions is probably one of the best, most profitable, and most scalable places to start applying AI in your business,” Diorio said in the conference session.
The most robust SRM solutions are built on an AI-driven platform that delivers core capabilities that include knowledge management, automation, project management, collaboration, content accessibility, and business intelligence.
The five buckets of AI implementation for customer response management
When most people think of AI today, they commonly think of GenAI, which can create content on demand, whether that’s written content for websites or blogs, or even photo and video content for product, social media, and sales materials.
When everyone can easily generate content with AI, it’s time to step back and look at more nuanced AI applications. “Responsive sees tremendous benefits that can be gained from this coming AI wave, not just in content, but in everything we do,” Shankar said at the virtual conference session.
AI is already bringing newfound speed and efficiency to every aspect of SRM. Shankar outlined what he called the “Five Buckets of AI Implementation.”
Content management
Effective content management (or knowledge management) is essential for maintaining accurate and up-to-date information. By implementing AI-driven content management systems, businesses can ensure their enterprise content remains relevant and reliable. This is key for mitigating risk as company knowledge is shared externally.
Features like auto-tagging streamline the organization of content by automatically assigning relevant tags to documents based on their content. Automated content refresh reminders ensure that critical information is reviewed and updated regularly — preventing outdated or inaccurate data from lingering in the system.
AI can also automate tasks such as content classification, version control, and metadata generation, further enhancing the efficiency and accuracy of content management.
Collaborative engine
A major benefit of AI in SRM is its ability to identify the right subject matter experts (SMEs) for any project. During the intake process, Responsive automatically finds the right SMEs based on specific content needs. This collaborative engine ensures that inquiries are directed to the right person, enhancing the accuracy and quality of responses, while also saving time for employees.
The efficiency gains are large for companies of all sizes, but for major enterprises with hundreds of thousands of employees distributed across the globe, an AI-driven collaboration engine is indispensable.
Workflow engineering
Identifying the right SME is only half the battle. Now you have to get them to contribute. SMEs may be busy, a Slack ping may have been missed, or the only person with the knowledge is out on vacation — but that request needs to be answered today because you only have 24 hours to turn around this high-value RFP.
That’s where Responsive’s intelligent workflow engine comes in. AI systems should be smart enough to make decisions based on certain triggers, such as automatically completing questionnaires, editing responses, and fine-tuning answers for RFPs.
For example, Responsive allows you to import questionnaires and then automatically map sections and questions using AI-enabled identification functionality. This process brings immediate structure to any response process, allowing users to tackle customer inquiries with more efficiency, speed, and compliance.
Project management
Every information request or proactive proposal requires project management. The largest RFPs require the speedy orchestration of dozens — if not hundreds — of moving parts. AI will be critical in simplifying project management to keep responses on track.
Responsive AI can manage responses for you, overseeing them end-to-end with time, scope, and resource management in mind. With tedious and difficult coordination off your plate, you get more time that you can apply to tasks that can really move the needle when it comes to winning customers – like personalizing responses.
Integrations
You cannot have an SRM platform that’s siloed. Without proper integrations, the most robust content library in the world will eventually become outdated, no matter how great of an AI engine you add on top of your knowledge base.
It’s important to integrate with multiple systems to ensure your content is up-to-date and current so that the AI can bring up the most current and compelling information to share externally with customers, prospects, partners, or investors. Responsive, for example, has a two-way integration with Seismic that ensures customer-ready sales content is always readily accessible.
How to get started with AI in SRM
Today’s world is filled with misinformation about AI that creates understandable misconceptions. Some thought leaders would have you believe that AI is simply useful for “doing your homework” or “making individual workers 10% more productive,” as Diorio said.
That’s certainly part of the equation, but it’s important to think about the bigger picture: creating and enabling AI systems that can efficiently take in information and accurately give responses.
“There’s a duality in AI,” Diorio said. “It doesn’t just happen. The data doesn’t just appear. It’s not clean, it’s not in the right place, and one individual in one silo can create some value, but many individuals in a workflow connecting the dots across the organization can create more.”
AI exists in an algorithmic world, and most customers see AI as Google-like: you type in a search query and you get a response. But Google is a complex business that addresses individual questions with publicly available information. Instead, businesses can and should use their own unique information, processes, customer behavior, and data sources.
Over time, your SRM solution becomes the central repository for all company knowledge, allowing users to quickly and seamlessly search for answers sourced from team members. With tools like Responsive LookUp, AI can further streamline your information retrieval process by surfacing the best answers from this central repository, complete with citations, ensuring accuracy and efficiency.
For example, when at a conference or even on a call, an employee can instantly pull up pertinent product or company details via the company’s extensive content library. As a result, businesses can handle more inquiries efficiently and enhance productivity — while mitigating the risk of sharing non-compliant information.
Responsive has that Google-like ease of use, but with algorithmic rigor, metadata, and all those core principles applied to an internal process with a much bigger business payoff: greater revenue.
So how should businesses actually start using AI in the SRM process to increase revenue?
Shankar suggests starting with managing customer-facing content, such as RFPs, which already contain hundreds of strong and valuable data points that are commonly reused. By building a knowledge base inside an SRM platform (with the help of AI, of course), organizations can centralize their most accurate and compelling information and ensure a strong foundation from which AI-powered responses can be generated.
Using AI to go from customer response to Strategic Response Management
AI is already transforming the way organizations share and exchange information with customers, creating significant business value and operational excellence. The exciting part is that – believe it or not – we’re still in the early days of this critical technology. The following years hold a lot of promise for additional advancements in AI that will bring even more efficiency to all aspects of Strategic Response Management.
By investing in an AI-driven SRM platform, businesses can improve efficiency, enhance customer experiences, and drive revenue growth. Just take a look at all of these proof points.
The conversation between Diorio and Shankar highlights the importance of starting with well-managed content and expanding AI applications to broader use cases. By taking practical steps to adopt AI in SRM, businesses can stay ahead of the competition and achieve sustainable growth.
To learn more about optimizing AI for SRM success, check out how Netsmart accelerated their response time by 10X with Responsive AI.
