Trend Watch: Key initiatives to get your enterprise AI-ready

AI is only as powerful as the fuel you feed it. True AI readiness means mastering your data's quality, governance, and accessibility. This is where competitive edge is born.

Trend Watch key initiatives to get your enterprise AI ready

28 Mar 2024

4 dk okuma süresi

AI is only as powerful as the fuel you feed it. True AI readiness means mastering your data's quality, governance, and accessibility. This is where competitive edge is born.

Equip your organization to benefit from AI advancements, prioritizing reinforcement of cybersecurity, data management, and AI guidelines. Whether your organization seeks to optimize daily workflows with AI or drive disruptive breakthroughs, a solid technological foundation is crucial for successful implementation.

What does it mean to be AI-ready?

Being AI-ready is more than having AI tools at your disposal. It requires a comprehensive technical foundation spanning various domains, which is a prerequisite for successful AI implementation and the creation of long-term value.

A robust and scalable IT infrastructure is the backbone of AI operations. This means having sufficient computing power (CPUs, GPUs, TPUs) for training and running AI models and efficient data storage and retrieval solutions (cloud storage, data lakes). It also involves establishing a well-defined AI architecture, which includes designing pipelines for data ingestion, pre-processing, and model training and frameworks for model deployment, integration, and management.

Trend Watch key initiatives to get your enterprise AI ready

High-quality data is the cornerstone of effective AI. AI readiness hinges on robust data management practices. This involves implementing data cleansing techniques to ensure data accuracy and consistency and establishing data governance frameworks to define ownership, access control, and security protocols for sensitive data. It also means considering data pipelines for real-time data integration with AI models, enabling continuous learning and adaptation.

Implementing security measures is vital to protect sensitive data used in AI models and to prevent unauthorized access or manipulation. Equally important is addressing the ethical considerations that come with AI development and deployment. These include mitigating bias in training data, ensuring fairness and transparency in AI decisions, and adhering to emerging AI regulations.

The real land of opportunities: Gen AI

Generative AI (gen AI) has transformed machines from mere tools into active collaborators. While Gartner's research reveals consistent intention to deploy AI solutions (between 17-25% of organizations annually between 2019-2024), actual implementation growth lags behind at only 2-5%.

To boost success rates, leaders must initiate the process by defining their organization's AI goals—where and how AI will be integrated. Considering modern AI's vast capabilities (decision-making, action, discovery, and creation), it's equally important to establish boundaries for its use. 73% of CIOs express intentions to increase their investments in AI in 2024 compared to 2023.

AI applications within an organization fall into two broad categories. Everyday AI streamlines existing workflows, boosting productivity and efficiency. Game-changing AI unlocks creativity, enabling the development of innovative products, services, or core competencies with the potential to transform entire industries.

Both categories offer value for internal and external applications. Defining your AI ambition requires carefully evaluating which internal and external use cases best align with your desired mix of every day and game-changing AI.

Trend Watch key initiatives to get your enterprise AI ready

To establish achievable AI goals, engage your team in exploring these three investment scenarios:

  • Prioritize readily available everyday AI tools for quick improvements in specific tasks. This approach maintains competitiveness but offers a limited long-term advantage.
  • Invest in customized AI applications with higher upfront costs and development time; the payoff is a distinct competitive edge.
  • Develop new AI-driven products and business models to aim for radical disruption. This high-risk, high-reward strategy requires significant investment but has the potential to transform your industry.

Deployment strategies

The recent surge in AI models and tools has inundated the market. Established software providers (ISVs) are rapidly integrating AI into their products, further widening the already overwhelming range of options. This competitive landscape, typical of emerging technologies, can make informed decision-making a challenge.

We observe the following deployment strategies:

  • Utilize gen AI within existing applications: Leverage established software with newly integrated image generation features, streamlining adoption.
  • Embed gen AI APIs for custom builds: Integrate Gen AI's foundation model APIs to develop unique applications.
  • Enhance gen AI via data retrieval: Employ Retrieval Augmented Generation (RAG) to incorporate external (often organization-specific) data, boosting accuracy and relevance for specialized tasks.
  • Fine-tune gen AI for specialization: Customize large, pre-trained foundation models using new datasets, impart domain knowledge, or refine performance.
  • Construct custom foundation models: Build bespoke models from the ground up, tailored precisely to your data and business objectives.

When doing so, you can rely on a partner like İnnova. The İnnovAI-DS decision support systems, driven by artificial intelligence, play a crucial role in helping companies gain a competitive advantage. InnovAI-DS enables companies to make highly accurate decisions, reduce the likelihood of errors, and subsequently enhance customer satisfaction and revenue.

Reshaping our creative world

Think of Gen AI as a tireless, uninhibited ideation machine. A brainstorming session that never sleeps.

This has profound implications for humans. GenAI challenges the very notion of "human-made," forcing us to ponder where inspiration ends, and imitation begins. As ideas become infinitely replicable, we must actively carve out new spaces for genuine, human-driven originality.

Trend Watch key initiatives to get your enterprise AI ready

Gen AI has the potential to level the creative playing field, offering greater opportunities for those outside traditional power structures. But with this potential comes immense responsibility. It's a wildcard, a catalyst for a future we can shape— or be shaped by.

The only certainty is that Generative AI forces us to choose. Will we be passive consumers swept along by this tide, or will we become AI-ready and seize the reins? The future will be defined not just by what generative AI can do but also by how we decide to use it.

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