Unless you have been off the grid or in hibernation for the last 10 months, you have heard of new innovations in Artificial Intelligence (AI). AI news has been ubiquitous and its impact in everyday’s life has been wide and far reaching already. And if you believe the experts, it's going to further disrupt everyone's lives – fundamentally in some cases.
However, the conversations have been mostly centered around impacts to individuals. While many enterprises recognize the huge potential of AI, they often find themselves struggling to effectively adopt and integrate AI into their business operations. The approach most enterprises are taking, based on our feedback from our customers, is “wait and see”. This may not be an option for businesses, AI is the new electricity that will disrupt every industry .
Organizations that invest in enterprise intelligence will find that they are more digitally resilient, agile, innovative, and dynamic than their peers.”–International Data Corporation (IDC)
Why You Soon Won’t Be Able to Avoid AI – At Work or At Home”–International Data Corporation (IDC)
In the following sections, we'll explore the reasons behind these struggles, the challenges that enterprises face when implementing AI, and some crucial considerations for successful AI adoption.
- Many AI models; Not Many AI models:
- It’s an oxymoron, but there are many thousands of AI models out there, but all predominantly focused on consumer use cases and are horizontal in nature
- There is a dearth of AI models that are focused on understanding Industry Business Processes and Industry specific structured and unstructured content and data
- Data Quality and Availability:
- High-quality data is the lifeblood of AI systems, but many enterprises grapple with volumes, inconsistent, incomplete, or low-quality data.
- Gaining access to relevant data can also be challenging due to data silos within organizations or regulatory constraints.
- Talent Shortage:
- AI /ML requires a specialized skill set that is in high demand but short supply. Finding and retaining qualified AI talent is a significant challenge for many enterprises as universities are only now spinning up courses.
- Enterprises are left with two options – either training the business leaders on data science or bringing in Data Scientists who may not be fully aware of the industry domain.
- Cost and ROI Concerns:
- Implementing AI solutions often requires substantial investments in technology, infrastructure, and talent.
- Measuring the return on investment (ROI) can be challenging, especially for long-term projects.
- Ethical and Regulatory Hurdles:
- Enterprises must navigate a complex landscape of ethical considerations and regulations surrounding AI, such as data privacy, bias, hallucination and transparency.
- Change Management:
- EIntegrating AI into existing workflows and convincing employees to embrace AI-driven changes can be met with resistance and pushback.
- Lack of Clear Strategy:
- Many enterprises rush into AI adoption without a well-defined strategy, leading to disjointed efforts and underwhelming results.
- Integration with Legacy Systems:
- Legacy systems may not be easily compatible with AI technologies, requiring substantial modification or replacement.
At OpenEnterprise.ai we believe we have found a way to allay some of the concerns by encouraging to adapt AI, instead of forcing it.
- Start with a Clear Strategy:
- Develop a comprehensive AI strategy that aligns with your business goals. Identify specific use cases and prioritize them based on potential impact and feasibility. We call them Process Hot Spots
- OpenEnterprise.ai can help with identifying those Hot Spots
- Walk, Crawl And Run:
- OpenEnterprise.AI has built a library of purpose-built AI models that can be introduced into your business processes a “drop at a time”, without having to introduce a brand new tech stack or changing the way businesses are conducted
- We have taken the approach of adapting AI models to empower – not replace – the users, by helping reduce manual intensive work.
- Data Rich, Insights Poor:
- Enterprises have already made huge investments in Data and Data warehouses . OpenEnterprise believes your data has insights that can help make your business processes more efficient.
- We believe Enterprises don’t need to do additional investments, but rather invest in adapting best practices
- We believe data insights can be mined without compromising data governance, and without having to break physical data silos
- We believe in Implementing data management practices to ensure that your AI systems have access to clean and relevant data.
- Power of AI at a business user's finger tips:
- OpenEnterprise aspires to create a simple framework (low or no code) that gives the business user power of introducing AI models into their day to day business, without having to hire a team of AI/LLM & Data Scientists
- Ethical AI Practices:
- Implement ethical AI principles from the outset. Ensure transparency, fairness, and accountability in AI decision-making processes.
- Train your models with your Data so you can be sure of the insights
- OpenEnterprise adapts RAG framework so you can be sure of the source, veracity and quality of outputs from the industry trained models
- Long-Term Vision:
- View AI adoption as a long-term investment rather than a quick fix. Be prepared for iterative improvements and updates to your AI systems.
- AI Governance Board
- Be clear who the exec sponsor is, ideally the CEO to drive a top down approach as this is an enterprise wide transformation.
- Establish an AI board of early adopters who will put in place a governance models for data , security, and employee training on ethics.
- Clear policies on what use cases you will pursue and which you will not
- AI augments enables employees to do higher work functions and have a human centered approach to AI.
AI is here to stay and it’ll impact the way we do business fundamentally. We can help you with your AI strategy.
Start a limited secure pilot project
- Start with small-scale AI projects to build internal expertise and demonstrate ROI. Use these projects as learning experiences to refine your AI adoption strategy.
We will love your feedback
Please do not hesitate to reach out if you would like to learn more or discuss any of our focus areas. I am thrilled about this journey and the road ahead!