Implementing Artificial Intelligence: Deriving Value at Every Stage

With so much focus on artificial intelligence’s potential to transform entire industries, it’s easy to feel overwhelmed or unsure about where to begin. The good news is that AI provides value at every stage of implementation, regardless of whether you’re just starting out or looking to scale advanced AI solutions. This article explores how businesses can unlock real benefits as they continue their AI journey, regardless of stage.

Even simple applications of AI—like using chatbots for customer service or basic predictive analytics in marketing—can offer improvements in efficiency and customer engagement.
Businesses that are aiming to expand their AI capabilities should focus on short-term wins (such as workflow automation and predictive maintenance) as well as long-term goals for broader adoption.
Advanced AI can power predictive analytics, personalized customer experiences, and even dynamic decision-making systems that continuously learn and adapt.

By Anne Valaitis

Introduction

Organizations often face challenges when it comes to implementing artificial intelligence (AI). With so much focus on AI’s potential to transform entire industries, it’s easy to feel overwhelmed or unsure about where to begin. AI research from Keypoint Intelligence shows that this is a common situation—although 47% of businesses are using basic AI tools like ChatGPT, only 14% are reporting deep use with embedded AI in their software tools.

Figure 1: Stage of AI Implementation

N = 454 Total Business Respondents

Source: The State of AI Readiness: A Comprehensive Benchmarking Analysis; Keypoint Intelligence 2024

The good news is that AI provides value at every stage of implementation, regardless of whether you’re just starting out or looking to scale advanced AI solutions. Many companies might feel stuck in the planning phase, but AI doesn’t require an all-or-nothing approach. With this understanding, businesses can unlock real benefits as they continue their AI journey—regardless of stage.

Foundational AI

AI doesn’t need to be complicated to deliver value. Even simple applications of AI—like using chatbots for customer service or basic predictive analytics in marketing—can offer significant improvements in efficiency and customer engagement. For example, automating routine customer interactions through AI chatbots can streamline service operations, reducing the burden on human employees and ensuring quick, consistent responses to common inquiries. This foundational level of AI is accessible and easy to implement, and it provides a clear starting point for organizations without requiring massive changes to infrastructure or processes.

Incremental AI

Once foundational AI tools are in place, the next step is to gradually scale AI’s capabilities. This involves integrating AI into more complex workflows where automation can drive deeper operational efficiency and data-driven decision-making. Keypoint Intelligence’s research validates this approach—among firms that are actively using AI, most are following a measured adoption path with 33% having used AI for 12–24 months and 29% having used it for 6-12 months. 59% of respondents cited enhanced operational efficiency as their key motivator, followed by improved customer experience and automating repetitive tasks.

Figure 2: Incremental AI Use

N = 454 Total Respondents

Source: Artificial Intelligence Readiness Survey; Keypoint Intelligence 2024

Workflow automation through AI can optimize repetitive tasks, manage scheduling, and even improve resource allocation. In marketing, AI can automate e-mail campaigns, customer segmentation, and personalized messaging—helping businesses enhance their outreach while minimizing manual intervention.

For businesses aiming to expand their AI capabilities, it’s essential to focus on short-term wins (such as workflow automation and predictive maintenance) as well as long-term goals for broader AI adoption. This balanced approach enables organizations to achieve measurable gains in business efficiency while preparing for advanced applications that can drive innovation. By scaling AI incrementally, businesses can avoid the risks of overhauling systems too quickly. Instead, they can gain insights from early AI implementations and adjust their strategies as they grow more comfortable with this technology.

Advanced AI

For firms that are ready to take things to the next level, advanced AI applications can revolutionize how they operate and engage with customers. AI can power predictive analytics, personalized customer experiences, and even dynamic decision-making systems that continuously learn and adapt.

At this stage, businesses are using AI to not only optimize existing processes, but to innovate and create new opportunities. For example, AI can help anticipate market trends, optimize supply chains, and deliver highly personalized products or services based on customer behaviors and preferences. AI-driven decision-making can also improve strategic planning, offering insights that human analysis alone might miss.

Overcoming Roadblocks

Many businesses encounter obstacles when planning their AI journeys. Common roadblocks include uncertainty about where to begin, concerns over the complexity of AI, or a lack of internal expertise. It’s important to remember that AI is a flexible, scalable tool—not an all-or-nothing proposition.

Here are some common challenges with advice on how to tackle them:

Uncertainty About Where to Start: AI implementation can seem overwhelming if you aren’t sure where to start. Begin with small, low-risk AI projects, such as automating customer service responses or integrating basic predictive analytics into marketing campaigns.
Lack of Internal Expertise:Partner with external consultants or AI vendors to help set up foundational AI systems. Over time, internal teams can build on this experience and gradually take on more complex AI initiatives.
Fear of Complexity:Focus on phased AI implementation. Start with automating individual processes and slowly expand AI’s role as your firm becomes more comfortable with the technology.

The Bottom Line

When it comes to AI, the key to success is recognizing that it doesn’t have to be a one-size-fits-all approach. There’s no need to implement a fully mature AI system all at once. Instead, view AI as an evolving journey where each phase can offer unique value. Whether you’re just starting out with basic tools or pushing the boundaries with advanced AI applications, the goal is to make incremental progress and learn along the way. By understanding that there’s value at every level of AI implementation, businesses can remove the barriers to entry and take practical steps toward a more efficient and innovative future.

As Principal Analyst for Keypoint Intelligence’s AI Service, Anne Valaitis draws on her document management and artificial intelligence expertise to help clients identify opportunities where AI can streamline operations, reduce costs, and shape new offerings that drive market demand and generate revenue. She has led numerous research projects that have influenced the document solutions landscape.