Generative Artificial Intelligence (GenAI) is on the brink of a massive expansion. IBM is seizing this opportunity and striving to cater to the escalating demand for this technology. The company has launched watsonx, an AI and data platform specifically designed for businesses, providing GenAI, data management, and AI model governance capabilities.
IBM’s strategic efforts go beyond mere product innovation. They include collaborative ventures aimed at stimulating growth across the industry. The company’s new partner program, IBM Partner Plus, is designed to establish a diverse network of resellers. This initiative is set to ignite growth and spur innovation in various sectors, highlighting IBM’s commitment to making AI accessible and enabling businesses around the globe.
IBM's Journey with watsonx and Responsible AI Governance
Partnerships and acquisitions frequently serve as turning points, transforming entire industries. This is exemplified by IBM’s 2019 acquisition of Red Hat, a prominent provider of open-source software solutions. This strategic move has fortified IBM’s standing in the open hybrid cloud solutions market while simultaneously offering both companies the chance to provide their clients with improved AI capabilities. IBM watsonx is an AI and data platform with a set of AI assistants designed to help organizations scale and accelerate the impact of AI with trusted data across the business. The platform offers flexibility, enabling organizations to start with one component or application and include additional ones as needs grow. It consists of a studio for foundation models, a data store, and a governance toolkit.
watsonx.ai
One of the core components of the watsonx platform includes watsonx.ai, a studio for foundation models, generative AI, and machine learning. The watsonx.ai studio provides a suite of open-source, third-party, and IBM-developed foundation models, training and tuning tools, and cost-effective infrastructure to streamline the entire AI model lifecycle. Its GenAI capabilities, such as content generation, retrieval augmented generation, summarization, and classification, offer operational flexibility. For example, organizations can use watsonx.ai to evaluate and sort customer complaints, review customer feedback sentiment, summarize text, capture critical points from financial reports, meeting transcriptions, etc., and extract information without pre-training the models to help enterprises in various operational areas. Organizations can further customize and train the models in watsonx.ai to improve performance on downstream tasks.
watsonx.data
Another component is IBM watsonx.data offers a fit-for-purpose data store built on an open data lakehouse architecture to scale analytics and AI with all the data, wherever it resides. This data management solution supports multi-cloud and hybrid cloud environments. It enables workload optimization through fit-for-purpose query engines that provide fast, reliable, and efficient big data processing at scale. With open formats, businesses can access and share all their data through a single entry point, eliminating the need for migration and duplication while reducing ETL (Extract, Transform, and Load) processes. Integrated vectorized embedding capabilities prepare large sets of trusted, governed data for ML, and GenAI use cases, such as Retrieval Augmented Generation (RAG). It integrates with existing databases, tools, and modern data stacks, ensuring compatibility and ease of use.
watsonx.governance
The need for responsible AI has become paramount as AI becomes increasingly integrated into business operations. IBM addresses this necessity through its ethical AI toolkit, IBM watsonx.governance, which allows businesses to direct, manage, and monitor AI activities. Software automation to streamline AI governance processes helps mitigate risks, manage regulatory requirements, and address ethical concerns for both GenAI and ML models. The toolkit enables process transparency by tracking and monitoring AI models across their lifecycle. It sets thresholds to detect inappropriate language or content in model inputs and outputs, triggering alerts when necessary. This helps businesses maintain control over their AI deployments and ensure they operate as intended.
Additionally, it facilitates effortless report generation by capturing and documenting model metadata through accessible factsheets, enhancing model explainability, and supporting audits. It also offers evaluation metrics for various tasks, such as text summarization and language translation, ensuring prompt accuracy and preventing the generation of harmful content. These metrics are documented within the factsheets for reference.
To address the risks associated with AI model hallucinations and data exfiltration, IBM has adopted a proactive strategy of developing smaller, specialized models tailored for specific business use cases instead of creating a single, large language model (LLM) for all purposes. These smaller models are designed to address issues related to hallucinations and latency more effectively. Furthermore, businesses heavily reliant on data, especially personally identifiable information (PII), encounter substantial risks from data exfiltration, which involves the unauthorized extraction of sensitive data from their systems. To address these risks, IBM strongly emphasizes core security principles like data discovery, encryption, and access management. Tools like Guardium and Security Verify are crucial in implementing and enforcing security measures and providing businesses with thorough data protection.
Looking ahead, IBM's AI strategy for 2024 remains centered on the watsonx platform and aims to democratize AI and empower businesses via tailored AI models. By prioritizing transparency and explainability, IBM ensures responsible AI usage and ethical decision-making, distinguishing itself from competitors.
A Use Case Approach to AI
Practical deployments of AI software products have transformed workplace efficiency and customer engagement. Some of the proven impacts achieved by watsonx include a 40% improvement in HR productivity, more than 90% of contact center cases involving conversational AI, and a 60% productivity gain in application modernization. These use cases have gained the confidence of businesses, showcasing the tangible benefits and potential for significant improvements in various operational aspects.
IBM watsonx Orchestrate, one of IBM’s AI assistants for enterprise productivity, seamlessly integrates with the tools used in human resource operations, spanning collaboration, communications, analytics, applicant tracking, and human capital management. It automates routine talent acquisition tasks such as posting job openings, scheduling interviews, and sending follow-up communication to candidates. Additionally, watsonx Orchestrate can create job description templates and share them with hiring managers, notify users of updates, provide lists of matching candidates, share alerts when qualified candidates apply, and send introductory messages.
In customer care, IBM provides watsonx Assistant, a conversational AI platform that empowers businesses to deliver seamless customer experiences. The solution offers capabilities such as creating an AI-driven engagement system and providing a 360-degree view of customers across service, sales, and marketing. This AI-based solution helps improve operations, drive growth, and increase customer satisfaction. Also, IBM's conversational AI platform leverages large language models to deploy efficient chatbots and voice assistants, automating routine interactions and directing complex queries to human agents, increasing accuracy, and delivering fast and consistent support.
Along with watsonx Orchestrate and watsonx Assistant, IBM has introduced a portfolio of watsonx Code Assistant products supporting enterprise application modernization and IT automation. These targeted AI coding assistants leverage generative AI to accelerate the software development lifecycle (SDLC), address skill gaps, and increase productivity by offering AI for Code capabilities, such as code generation and code translation, combined with end-to-end automation frameworks and tooling.
At IBM, the distinction lies in being the sole major consultancy integrated within a technology company. Guided by open innovation, collaboration, and trust principles, IBM doesn't simply offer advice; it actively partners with clients and collaborators to shape, construct, and manage high-performance businesses. This integration enables IBM to provide end-to-end solutions to clients, addressing technological challenges and strategic and organizational aspects of AI implementation.
It is also worth noting that IBM is focusing on enhancing its solutions and offerings and prioritizing employees' well-being by introducing IBM Consulting Advantage. This AI-powered platform is designed to strengthen IBM consultants' capabilities, ensuring consistency and agility in client service delivery.
With the help of this platform, employees can leverage strategy assistants to streamline use case prioritization, business case development, business analyst assistants can facilitate the creation of user personas for user-centric design, and developer assistants can expedite code generation and conversion processes. Notably, IBM Consulting Assistants offer an added layer of privacy and security, as these assistants are also equipped with mechanisms to detect and flag any personally identifiable information (PII) within prompts, ensuring compliance with privacy regulations.
Strategies for SMBs and Midmarket firms
Realizing SMBs’ resource constraints, tech companies are actively working to provide solutions tailored to their needs. IBM’s watsonx AI and data platform utilizes qualitative and quantitative data to create personalized experiences for SMBs. By analyzing customer trends, market forces, and historical transactions, it can recommend products tailored to each business’s specific needs, driving increased value and enhancing the customer experience.
According to a recent survey by Techaisle, which included over 3000 Small and Medium Businesses (SMBs) and Midmarket firms, deploying Generative AI (GenAI) applications varies significantly across different business sizes. The survey found that only 4% of small businesses have deployed some GenAI applications. This figure rises to 14% for SMBs, 22% for core midmarket firms, and 63% for upper midmarket firms.
However, several challenges hinder the broader deployment of GenAI. These include high costs, insufficient technology infrastructure, potential risks and privacy threats, and a need for more skilled talent for development and implementation. Collectively, these factors represent the primary obstacles in the path of GenAI deployment.
Thus, solutions like watsonx Code Assistant for Red Hat Ansible Lightspeed help meet technical needs while reducing development efforts and driving increased productivity. In addition, it provides a consumption-based pricing model, which strategically aligns with the specific needs of SMBs. With consumption-based pricing, SMBs pay for actual usage. The platform also offers self-service platforms and conversational AI solutions such as watsonx Assistant, which enable SMBs to perform tasks such as updating billing and contact information without needing to contact a representative. This increases efficiency and improves the overall customer experience.
Despite an increasing interest in AI among SMBs, there needs to be more awareness regarding the need for AI governance. This creates challenges like disparate tooling, poor collaboration, and difficulty assessing AI needs. With lifecycle governance, risk management, and compliance capabilities, IBM offers a customizable AI governance solution addressing these challenges. Additionally, IBM provides services to guide clients through their AI journey, from needs assessment to deployment. Techaisle's survey shows that 57% of SMBs and midmarket firms seek AI assessment guidance. This underscores the role of AI governance for SMBs and the potential of IBM's solution to empower them in their AI efforts.
SMBs and Midmarket firms will require a flexible adoption strategy to navigate the challenges. Internally, the key will be to increase the capacity for change within the organization. Externally, these firms will leverage open-source and free large language models alongside "AI-as-a-service" platforms to obtain cost-effective access to Gen AI's capabilities. On the supply side, this shift will further increase cloud consumption within the SMB segment. AI-infused, AI-embedded business applications will gain traction among SMBs, while end-to-end platforms will challenge the dominance of best-of-breed solutions.
An Open Ecosystem Approach with Collaboration and Channel Initiatives
By partnering with industry leaders such as SAP, Salesforce, AWS, and many more, IBM is trying to embed watsonx.ai seamlessly into diverse solutions and drive efficiency, productivity, and innovation across sectors.
The partnership between Hugging Face and IBM aims to assist businesses in constructing, deploying, and tailoring foundational models across various domains. Within the watsonx.ai environment, AI developers can utilize models from both IBM and the Hugging Face community. These models come pre-trained to handle multiple Natural Language Processing (NLP) tasks, such as question answering, content generation and summarization, text classification, and extraction.
IBM has also collaborated with Meta to integrate the latter’s Llama 2 LLM into the watsonx.ai studio, providing IBM partners with easy access to the LLM. In December 2023, the two companies announced the formation of the AI Alliance, a group of 70+ industry and academic leaders coming together to advance open, safe, and responsible AI.
The company is also expanding its relationship with AWS, integrating its watsonx platform with AWS to meet client demand for GenAI capabilities and offering watsonx solutions on the AWS Marketplace. Additionally, IBM and SAP have teamed up to integrate IBM watsonx capabilities into SAP Start, SAP's digital assistant, enabling users to access NLP capabilities and predictive insights, enhancing productivity, and facilitating faster decision-making processes. These AI-driven capabilities extend across various SAP solutions, allowing managers and employees to automate routine tasks, improve productivity, and focus on essential tasks.
Further, IBM understands the crucial role played by its partner network in fostering innovation and driving business growth. Thus, the IBM Partner Plus program was launched to cater to various partners, including resellers, hyperscalers, and systems integrators. This program aligns with the company’s hybrid cloud and AI strategy and offers transparent tiers—Silver, Gold, and Platinum—based on partners' technical expertise and sales records. Its key features include a centralized IBM partner portal for tracking partners’ performance and offers partners access to a comprehensive set of tools and resources designed to support their success. These resources may include training materials, sales and marketing collateral, technical documentation, and support services. Furthermore, with the launch of Partner Plus, IBM is providing incremental funding, personalized support, expanded investment allocations, and access to new market opportunities to Gold and Platinum tier partners. These resources and initiatives empower partners to execute more effective marketing strategies, reach a wider audience, and capitalize on emerging opportunities, driving faster and more sustainable business growth.
IBM has adopted an open ecosystem approach in AI by partnering with its competitors and leveraging diverse expertise and resources to drive AI innovation and meet clients' evolving needs across industries. This strategy strengthens IBM's position in the market and fosters a collaborative environment where innovation thrives.
Final Techaisle Take
The upward trajectory of GenAI’s growth opens up significant opportunities for enhancing business operations. IBM’s strategic acquisition of Red Hat in 2019 has fortified its standing in the hybrid cloud solutions market, enabling it to provide sophisticated AI capabilities via platforms like watsonx. Integrating GenAI and Machine Learning techniques with watsonx.ai allows businesses to craft, implement, and manage AI systems that cater to their specific needs. As IBM continues its journey with watsonx and responsible AI governance, it emphasizes making AI accessible to all and empowering businesses globally. This strategy fuels innovation and underscores the importance of deploying AI ethically and responsibly, ensuring transparency, explainability, and ethical decision-making. Moreover, IBM Consulting and its technological products play a pivotal role in maintaining IBM’s competitive advantage. IBM is dedicated to providing AI solutions, fostering growth and innovation across the industry through collaborative partnerships and an open ecosystem approach.