Businesses often face challenges when starting or ramping up AI implementation, including uncertainty about how to approach it or where to begin. A big bang approach is often ineffective and costly. Instead, businesses should adopt an incremental approach, emphasizing strong data quality and a single source of truth (SSOT). It is crucial to protect internal and external data platforms and tools from the constant threat of ransomware and hacking. Business ownership, selecting high ROI use cases, and engaging all stakeholders will help drive success.
Understanding the customer’s key challenges, maturity level, and the relationship between IT and the business leads to a more effective roadmap. Common challenges impacting ROI calculations for AI initiatives include a lack of detailed requirements, limited understanding of opportunities, uncertainty about approaches, difficulty prioritizing use cases, inconsistent data across systems, disparate legacy infrastructure, and having a sense of risk assessment needs.
These challenges often make businesses hesitant about investing in data quality and AI initiatives, as they struggle to clearly understand and quantify potential returns. Altimetrik’s Digital Business Methodology (DBM) breaks down complex projects into manageable bite-sized components and, through collaboration across stakeholders, help assess their maturity level and select relevant case studies.
This approach requires a centralized data cloud platform for end-to-end automation with data and AI engineering rigor, including governance, security, and compliance. Centralized cloud platforms, such as Snowflake and Databricks, provide the necessary infrastructure to create and manage data assets efficiently, ensuring consistency, speed, and scale. The combination of a Digital Business methodology and the platform is instrumental in helping businesses engage and achieve success with AI. This is done within the customer’s environment but remains independent of their complex and siloed systems.
Key steps in the process include conducting an initial evaluation of the customer’s current data and AI capabilities, identifying the biggest challenges and opportunities, and prioritizing use cases based on potential ROI and ease of implementation. It also involves considering the customer’s maturity level when selecting appropriate case studies, discussing the customer’s readiness for investments in infrastructure and software, and showcasing examples of how Altimetrik has helped similar companies achieve success in their data and AI journey. It is important to highlight case studies that demonstrate quick wins and tangible ROI to build confidence is also crucial. The selection of case studies is based on the specific challenges and goals of the business.
Managing organizational change is another critical factor for successful AI adoption. Businesses should invest in training programs to develop the necessary skills within their workforce for data and AI projects. For example, one of the challenges is that technology teams typically want detailed requirements upfront and may not understand the business opportunity. Engaging the business to align on priorities will help inform investment decisions related to data quality and AI. By demystifying this process the business can take the ownership and, working with technology, can quickly align and execute the strategy.
By taking this approach, Altimetrik can help customers understand their data and AI maturity and provide relevant examples to guide their next steps. Our Digital Business methodology alleviates costly investments, uncertainty, and helps businesses see the potential of AI, leading to improved ROI and customer satisfaction. This unique approach is a differentiator, identifying key functional and industry-specific use cases that enhance growth with consistency, scale, and speed. This approach integrates SSOT, AI tools, and GenAI that leverage large language models (LLMs) to attain ROI with minimal investment, tailored to specific business needs, and is supported by end-to-end automation and DevSecOps principles.
The convergence of data and GenAI/AI technologies within a business-led ecosystem marks a significant change in the market. This shift from digital transformation to Digital Business is crucial, focusing on creating new digital revenue streams and operational efficiency (IDC). A business led approach and ownership of data quality and use case selection will inform investment prioritization an demystify GenAI/AI.
Altimetrik, at the core of this integrated ecosystem, is uniquely positioned to drive business engagement and outcomes through its strategic partnerships and innovative platforms. By harnessing the collective expertise of data tech partners, CRM providers, cloud companies, and GenAI/AI tool companies, Altimetrik is setting new standards for creating immediate and impactful use case development that deliver tangible business results.
