VP-IT at rSTAR, spearheading business and IT transformation for customers with a focus on manufacturing, energy/utilities and construction.
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Although the initial enthusiasm that greeted the arrival of platforms such as ChatGPT has calmed down, interest has only increased among leadership in enterprise-level organizations. Gartner states that out of 1,400 executive leaders surveyed in the third quarter of 2023, 45% reported that their organization is piloting or experimenting with generative AI (GenAI).
With more organizations expected to adopt the solution this year, there has been a commensurate increase in GenAI tools, platforms and more in the marketplace.
Although GenAI continues to offer many benefits, there are still risks, uncertainties and important considerations for enterprises seeking to adopt it. As more organizations look for ways to add GenAI, it is crucial to understand how to choose the right GenAI platform to maximize success.
My company, rSTAR Technologies, has worked in the field of AI for several years. We routinely help large enterprises examine and evaluate the features of AI solutions under consideration. Based on this experience, here is my perspective on how to choose the best GenAI platform for your company:
Define project objectives.
Companies must evaluate their challenges and assess the business impacts of adopting GenAI.
There are diverse GenAI adoption objectives: process automation, customer engagement, call deflection, productivity, omnichannel CX, etc. Defining project goals, objectives and values based on business challenges provides guidelines for evaluating potential solutions.
Understand existing company data and systems.
GenAI systems must base decisions and conversations on existing data. The quality of the source data is vital to the success of AI projects. Here are some crucial questions when evaluating your existing data:
• What’s the data type and quality?
• Is data consolidated?
• Where is data located?
• What is the integration infrastructure?
• What models and capabilities suit the data and systems?
• What performance parameters are expected?
• Which platforms are best for the industry?
Evaluate model capabilities.
Models are a critical part of a GenAI solution. Evaluate platforms that can support diverse model types and architectures and have suitable capabilities for your existing data and systems.
A good platform should be able to train, test and deploy diverse models and optimize performance and efficiency. The platform should be able to pre-process, clean and augment data with privacy, safety and security considerations in mind.
Consider performance, scalability and future-proofing.
Performance, scalability and future-proofing are crucial factors when choosing a GenAI platform.
The platform should meet the company’s objectives and scalability features and easily adapt to changing business needs, data volumes, data velocities and models. Also, consider future changes in the platform’s features and offerings that may significantly affect the usage of the GenAI solution.
Review ease of integration and compatibility.
Reviewing the ease of integration before adopting a platform reduces frustrations and project implementation failure. It’s crucial to evaluate the platform’s test readiness to assess if it’s an out-of-box, plug-and-play solution and, if not, to understand the integration complexity.
Assess the platform’s ability to integrate and communicate with other systems like CRM tools, data sources, analytics tools, content management systems, social media platforms, etc. Also, review compatibility with different devices and assess support for different formats and standards like XML, JSON, HTML, etc.
Evaluate UI/UX and accessibility.
A good GenAI platform should be accessible to developers, designers, business users, analysts and other stakeholders. It should have a good UI/UX and simplified and automated GenAI workflow from data ingestion to model creation and output generation.
Similarly, documentation, tutorials and support should help users learn, troubleshoot and optimize their platform usage.
Check reputation, credibility, innovation and differentiation.
Vendors offering GenAI platforms should demonstrate expertise and authority, provide evidence and testimonials of successful projects and clients and be able to build trust and confidence.
The platform should offer innovative and differentiated solutions that stand out and deliver value. There should be unique and novel features and functionalities like multimodal generation, customer models and interactive outputs. A good platform can help an organization showcase brand values, identity, personality and other differentiation through the GenAI output.
Understand cost considerations.
Check for platforms that have a cost-effective solution with flexible pricing and payment options. Evaluate the different pricing options and decide what works for the organization’s objectives and budget.
Also, assess the platform’s ability to provide optimal output by delivering high-quality, fast and efficient GenAI solutions while reducing the time and resources required.
Evaluate ethical considerations and define responsibilities.
Ethical considerations are also an important component of selecting a GenAI platform.
Choose platforms that mitigate potential risks like bias, plagiarism, misinformation and privacy breaches. Assess transparency and accountability and the solution’s ability to provide accurate, quality and credible outputs. Additionally, evaluate the platform’s compliance with relevant laws, regulations, best practices and standards.
Be sure to ask questions about the different risks and concerns and clearly define risk management roles and responsibilities amongst stakeholders.
Assess security and privacy measures.
Assess the platform’s security and privacy infrastructure to ensure they provide secure, reliable and trustworthy GenAI solutions that protect models, data and outputs from unauthorized access and manipulation.
A good platform implements robust security measures like encryption, authorization, authentication and auditing and has backup and recovery options as well as other infrastructure to ensure availability and continuity.
Check for feedback and improvement structures.
Consider platforms that have feedback and improvement structures in place to facilitate product improvement. Also, ask: How does the platform monitor and update models and applications to adapt to the latest GenAI advancements and trends?
Explore options fully.
There is no one-size-fits-all when adopting a GenAI platform. Conduct in-depth research, consult experts and stakeholders, experiment and iterate to determine what works for your organization.
The right GenAI platform meets your needs and objectives without significant cost, security, ethics and privacy implications. By carefully assessing these factors, you can more effectively pinpoint the GenAI platform that matches your particular needs and objectives.
Finally, testing or prototyping the platform in your environment before making a long-term commitment is frequently advantageous.
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