Author: Rena Bhattacharyya

Rena is a Director of Custom Research at Current Analysis, specializing in Delivery Management. She is responsible for ensuring the delivery of actionable recommendations and guidance to clients to assist them in formulating their market development and execution strategies. Her expertise is in telecommunications and IT services, including business networking , communications, data center, security, and business continuity services.

Meta Will Need to Shed its Consumer-centric Image to Gain Ground in Enterprise AI

by Rena Bhattacharyya, posted in Big Data
A woman with long, dark hair wearing a gray blazer, smiling at the camera.
R. Bhattacharyya

Summary Bullets:

• Meta will need to shed its consumer-centric image to gain traction in the business market, even if it only targets smaller organizations.

• Convincing organizations that they can trust Meta to secure personal information and corporate intellectual property will take time and effort.

On Monday September 28, 2026, Meta announced plans to enter what is already a crowded enterprise AI market. It will develop Meta Enterprise Platform, a collection of tools and services that will help business customers implement their own AI strategies. Few details were shared other than the platform will incorporate Muse agent, Meta Business Agent, Muse API, Muse Code, and other solutions.

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Google’s New Tools Support ‘Value Maxxing’ to Address Organizations’ Growing Concern Over AI ROI and Tokenomics

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• After a period of ‘token maxxing,’ organizations are looking to reign in and better control inference costs.

• Instead, enterprises are now embracing ‘value-maxxing,’ which focuses on outcomes.

Last week, Google announced several enhancements to Gemini Enterprise designed to help enterprises obtain greater and faster ROI on their AI projects. The improvements address one of the biggest frustrations expressed by organizations today, namely that the benefits promised by AI are taking too long to realize. Companies are clamoring for domain specific solutions in order to speed the deployment, reduce the integration complexity, and increase the value obtained from AI projects. Additionally, business leaders are eager for better tools to help them manage AI costs. They are looking for improved visibility on token use and costs, more proactive spending controls, and more flexible payment options.

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HCLTech Hones Its Application Development Practice, Reflecting the Disruptive Impact of AI

by Rena Bhattacharyya, posted in Cloud Enable
A woman with long, wavy dark hair and a warm smile, wearing a gray blazer and a silver necklace, posed against a neutral background.
R. Bhattacharyya

Summary Bullets:

• AI has disrupted traditional developer teams and tasks, and new processes and talent will be required to responsibly implement the intelligent automation and probabilistic nature of agentic systems.

• As enterprises drive towards a mature application landscape that is built using AI and for AI-infused applications, intelligent orchestration and integration are critical.

Although AI offers the promise of greater efficiency across a myriad of enterprise workstreams, one of the use cases with the greatest benefit is application modernization. GenAI’s effectiveness in writing and refactoring code has already been highly touted in mainstream media; less known is its use in other aspects of the software development lifecycle (SDLC). It can be used for discovery, documentation, quality assurance, autonomous testing, intelligent orchestration, and other tasks as well. Furthermore, AI is doing much more than accelerating application development; it is changing how software is engineered. Intelligence and analytics are no longer add-ons that are layered onto existing applications. Today’s applications have intelligence embedded into their workflows and decision logic, essentially creating modern apps that are designed to be AI-first.

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AI Agents Take Center Stage at Salesforce TDX25

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

  • Salesforce’s new AgentExchange is a marketplace for AI agents that are preconfigured to integrate seamlessly.
  • Interoperability among agents and frameworks will be a key concern as organizations look to deploy multiple agents to complete more complex tasks.

Salesforce’s annual developer conference, TDX25, took place in San Francisco during the first week of March. As expected, AI played heavily in all conversations, with AI agents and Salesforce’s Agentforce platform taking a starring role. Similar to its approach with GenAI, Salesforce has been a thought leader when it comes to AI agents. Noteworthy announcements from Salesforce TDX25 included Agentforce 2dx (a suite of AI-powered tools to support building, testing and deploying AI agents), an Agentforce API (enabling customers to embed Agentforce across applications and workflows), partnerships to help scale deployment of AI agents, and customer testimonials and potential use cases.

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Telefonica Tech’s Expanded AI Portfolio Helps Enterprises Deploy GenAI for Virtual Assistants

by Rena Bhattacharyya, posted in Communicate
R. Bhattacharyya

Summary Bullets:

• A key benefit of the Telefónica Tech generative AI (GenAI) platform is that it provides access to and evaluates large language models (LLMs) from multiple sources, including hyperscale cloud providers and open source models.

• Telefónica’s advantage comes from its existing customer relationships and its ability to promote a vendor-agnostic environment.

On January 28, 2025, Telefónica Tech announced its GenAI platform to help enterprise customers create virtual assistants. The platform is designed to be easy to use while at the same time allowing access to multiple LLMs. It provides tools for evaluating models based on cost, performance, and latency. Use cases include virtual assistants for customer services, enhanced data analysis, and improved efficiency in departments such as human resources and finance.

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HCLTech Builds Customer Confidence by Offering Outcomes-based Pricing Models for Generative AI (GenAI)

by Rena Bhattacharyya, posted in Big Data, IT Leader
R. Bhattacharyya

Summary Bullets:

• HCLTech is taking a wise approach to building customer confidence in its GenAI services by offering outcomes-based pricing models.

• Tying compensation to performance, which can include KPIs and ROIs, is a logical next step.

GenAI is considered the most disruptive technology in the market today. Momentum is strong, with the market opportunity expected to grow from $2.8 billion in 2023 to $75.7 billion in 2028, a CAGR of 94%, as projected by GlobalData’s latest forecast. Enterprises across a range of industries are eager to harness the benefits of GenAI in a wide variety of use cases. The technology can be used to support customer service and marketing initiatives, improve operational efficiency, enhance security and fraud prevention measures, modernize applications, and much more.

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Generative AI Watch: Text-based Data is the Next Logical Evolution of Synthetic Data

by Rena Bhattacharyya, posted in Big Data

Summary Bullets:

R. Bhattacharyya

• Synthetic unstructured data, or text, can be used to train and finetune large language models (LLMs) used in customer support applications or chatbot conversations.

• The application of synthetic data, both tabular and unstructured, will continue to grow, driven by a need for additional training data as well as concerns over data privacy.

On October 1, 2024, MOSTLY AI announced that its platform can help enterprises create synthetic text, a timely new capability given the growing interest by enterprises to leverage GenAI to extract insights from unstructured data. Over the past several years, much of the conversation around synthetic data has focused on using GenAI to create synthetic tabular data. Tabular data is structured data that can be neatly organized, for example information that can be arranged in an excel file. The logical next step is to use GenAI to create text-based information that can be used to customize LLMs.

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Generative AI Watch: Telefonica Tech Collaborates with IBM to Help Customers Navigate GenAI

by Rena Bhattacharyya, posted in Big Data, Cloud Enable, Communicate
R. Bhattacharyya

Summary Bullets:

• The complexities of implementing generative AI (GenAI) and integrating it with existing systems present a challenge to enterprises; most organizations report that deployments take much longer than originally anticipated.

• Telefónica Tech is wise to expand its AI offerings for business customers and to offer tools focused on data management and governance.

On June 18, 2024, Telefónica Tech announced it was expanding its partnership with IBM to help businesses in Spain adopt artificial intelligence (AI), including GenAI. The companies will offer Shark.X, a platform designed for data management, analytics, and AI. The platform will incorporate key technologies from IBM, including IBM Cloud Pak for Data and IBM watsonx AI and Data. However, the partnership is not limited to hardware and software: The companies will work together to provide training and educational programs as well as to develop use cases and to help customers implement pilot projects.

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Ericsson Flexes Increasing US Strength with 5G Factory, Federal Contract, and AT&T Win

by Rena Bhattacharyya, posted in Internet of Things
R. Bhattacharyya

Summary Bullets:

• Ericsson is investing to solidify and expand its US presence and ecosystem of partners to gain an edge over competitors based overseas.

• Ericsson’s messaging reflects the evolving domestic political climate and changing global geopolitical environment.

In late May 2024, Ericsson hosted industry analysts to its 5G smart factory in Dallas, Texas (US). The key theme of the event was that Ericsson provides “5G made in the US, for the US.” The Swedish telecom equipment provider reminded attendees that it has been operating in the US for 122 years and that 26% of its sales are from North America. Furthermore, it maintains six R&D facilities, employs 7,600 people, and has invested over $7 billion in acquisitions in the region. In March 2024, the company formed a new division, Ericsson Federal Technologies Group, to help the US federal government deploy 5G solutions. Via its Dallas facility, Ericsson meets the government’s requirements to support open RAN technologies and equipment manufactured in the US.

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Generative AI Watch: Small Language Models’ Growing Role in a Multi-Model World

by Rena Bhattacharyya, posted in Big Data

R. Bhattacharyya

Summary Bullets:

  • As training techniques improve, small language models (SLMs) are becoming more and more accurate, increasing their appeal.
  • The smaller models make sense for simpler tasks; they can work offline and are a good alternative when organizations want to process information close to the source of collection.

The generative AI (GenAI) landscape has been evolving at breakneck speed since OpenAI exploded onto the scene in late 2022.  And despite the numerous new GenAI solutions and product enhancements already brought to market in the last 18 months, momentum around natural language processing (NLP) shows no signs of slowing down. The latest buzz worth paying attention to is around SLMs, which offer capabilities similar to large language models (LLMs) but require far less training data and processing power.  Easier to adopt, less expensive to run, and with a smaller carbon footprint, these models hold the potential to further accelerate the already rapid pace of GenAI adoption.

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